[{"_1":2,"_355":-5,"_356":-5},"loaderData",{"_3":4,"_12":13},"root",{"_5":-5,"_6":7,"_8":9},"user","hasAccess",false,"h1bUi",{"_10":7,"_11":-5},"enabled","userId","routes/jobs",{"_14":15,"_15":16,"_94":43,"_95":96,"_100":-5,"_101":102},"kind","job",{"_17":18,"_19":20,"_21":22,"_23":24,"_25":26,"_27":28,"_29":-5,"_30":-5,"_31":32,"_34":35,"_36":37,"_38":37,"_39":-5,"_40":41,"_42":43,"_44":45,"_46":47,"_48":7,"_49":50,"_51":-5,"_52":53,"_55":56,"_58":-5,"_59":60,"_72":73,"_74":75,"_76":77,"_78":-5,"_79":-5,"_80":-5,"_81":-5,"_82":83,"_84":-5,"_85":7,"_86":87,"_88":7,"_89":90,"_91":-5,"_92":93},"id","c9ebabeb-af69-43ad-8238-fad9974c36be","title","Senior Machine Learning Engineer","url","https://jobs.lever.co/coderio/dff064ee-d76d-4bab-ab4d-c8922afc240c","job_description_full","","job_description_summary_short","Senior Machine Learning Engineer role focused on machine learning engineering.","job_description_summary_long","The posting identifies a Senior Machine Learning Engineer position. No responsibilities, qualifications, technologies, benefits, work arrangement, or compensation details are provided.","employment_type","compensation","seniority",[33],"senior","date_posted","2026-08-18T18:25:27.008+00:00","created_at","2026-09-05T10:36:31.323323+00:00","updated_at","deleted_at","company","Coderio","company_slug","coderio","profile_pic_url","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/fda04184-bc83-4053-98ee-76d0fe291228.png","career_category","Software Engineering","sponsors_h1b","headcount_range","RANGE_201_500","latest_funding_class","location_ids",[54],1032717330,"sub_categories",[57],"ML Engineering","tech_stack","locations",[61],{"_17":54,"_62":63,"_64":65,"_66":67,"_68":69,"_70":71},"city","Buenos Aires","slug","buenos-aires-arg","state","Buenos Aires, Ciudad Autónoma de","country","Argentina","country_iso3","ARG","requirements",[],"responsibilities",[],"benefits",[],"salary_minvalue","salary_maxvalue","salary_currency","salary_unitText","credential_category","no-requirements","months_of_experience","experience_in_place_of_education","home_page_url","https://coderio.com","company_sponsors_h1b","h1b_sponsorship_status","unknown","h1b_sponsorship_evidence","company_id","fda04184-bc83-4053-98ee-76d0fe291228","companySlug","companyInfo",{"_17":93,"_97":41,"_64":43,"_86":87,"_98":43,"_49":50,"_99":-5},"name","linkedin_slug","description","h1bHistory","similarJobs",[103,147,200,249,296],{"_17":104,"_19":105,"_21":106,"_23":107,"_25":108,"_27":109,"_29":-5,"_30":-5,"_31":110,"_34":111,"_36":112,"_38":113,"_39":-5,"_40":114,"_42":115,"_44":116,"_46":47,"_48":7,"_49":117,"_51":-5,"_52":118,"_55":119,"_58":120,"_59":125,"_72":127,"_74":136,"_76":143,"_78":-5,"_79":-5,"_80":-5,"_81":-5,"_82":83,"_84":-5,"_85":7,"_86":146},"1791b65b-e10a-414a-b142-344dc546f5e8","Machine Learning Engineer","https://mercadolibre.eightfold.ai/careers/job/43826413-machine-learning-engineer-buenos-aires-argentina","

Como Machine Learning Engineer en Mercado Libre, diseñarás y escalarás sistemas innovadores y seguros que resuelven problemas reales y de alto impacto. Trabajarás en un entorno dinámico con tecnología de vanguardia, aplicando buenas prácticas de ingeniería, modelos de IA propios y aprendizaje continuo, con el propósito de democratizar el comercio electrónico y los servicios financieros en América Latina.

Imagináte emprendiendo proyectos desafiantes, dinámicos e innovadores y siendo responsable de:

Diseñar y evolucionar soluciones de Inferencia de Baja Latencia: Llevar modelos de Computer Vision y NLP a producción optimizando el throughput y el consumo de recursos, garantizando tiempos de respuesta compatibles con la experiencia en vivo.
Dominar el ciclo de vida de LLMs/VLMs: Desde la exploración y el context engineering hasta la implementación de flujos agénticos que puedan razonar sobre contenido multimedia.
Garantizar la calidad mediante Evals: Construir pipelines de evaluación rigurosos para medir de forma reproducible el impacto de cada cambio en los modelos, prompts o flujos, mitigando regresiones y alucinaciones.
Iterar sistemáticamente: Aplicar técnicas de prompt learning e iteración continua basadas en datos para maximizar el recall y la precisión de nuestras soluciones.
Diseñar Arquitectónicamente y Spec Driven Development: Liderar la definición de componentes y contratos claros utilizando Spec Driven Development antes de escribir código, asegurando sistemas robustos, testeables y mantenibles en el tiempo.
Construir el motor de datos: Desarrollar los pipelines de datos necesarios para alimentar el entrenamiento, fine-tuning y evaluación continua de los modelos.

¿Cuáles son los requisitos?

Dominar el ciclo de vida completo de modelos de Computer Vision y NLP, entrenamiento, evaluación e inferencia.
Tener experiencia optimizando y sirviendo modelos para baja latencia utilizando PyTorch, HuggingFace, formatos de serialización como ONNX, y motores de inferencia modernos de alto rendimiento como vLLM o Llama.cpp.
Contar con experiencia real en el ciclo de vida de soluciones basadas en LLMs: técnicas avanzadas de Context Engineering, RAG, y metodologías sistemáticas de Prompt Iteration / Prompt Learning.
Demostrar experiencia en el desarrollo de flujos agénticos y orquestación compleja utilizando LangChain, LangGraph o el Google SDK. Tener experiencia configurando y analizando métricas con frameworks de Evals para LLMs (ej. LangSmith, Ragas u homólogos).
Manejar técnicas de Fine-Tuning eficiente de modelos como QLoRA para ajustar modelos fundacionales a nuestros casos de negocio.
Tener dominio avanzado de Python aplicando buenas prácticas de ingeniería de software: Clean Architecture, testing automatizado y pipelines de CI/CD.
Tener experiencia en la creación de pipelines de datos masivos usando BigQuery y SQL avanzado para extraer datasets de entrenamiento y evaluación.

¿Te animás a dejar huella en la tecnología de América Latina?

¡Postulate y sumate a nuestro propósito!

Modalidad de trabajo híbrida. Site Bogotá, Colombia.

","Machine Learning Engineer responsible for building and scaling low-latency Computer Vision, NLP, and LLM/VLM systems for high-impact e-commerce and financial services use cases. The role combines model serving, evaluation, agentic workflows, prompt iteration, fine-tuning, and large-scale data pipelines in a hybrid Bogotá environment.","The role covers the full lifecycle of Computer Vision, NLP, LLM, and VLM solutions, from exploration and training through evaluation and production inference. Responsibilities include optimizing low-latency model serving, building rigorous evaluation pipelines, developing agentic workflows, applying context engineering and prompt learning, and creating data pipelines for training and fine-tuning. Candidates should have advanced Python skills and experience with PyTorch, HuggingFace, ONNX, vLLM or Llama.cpp, LangChain or LangGraph, LLM evaluation frameworks, QLoRA, BigQuery, and SQL. The engineer will also lead architectural definitions using clear contracts and Spec Driven Development while applying automated testing and CI/CD practices. The position is hybrid and based at the Bogotá, Colombia site.",[33],"2026-08-31T16:48:28+00:00","2026-09-03T01:28:18.960567+00:00","2026-09-04T22:33:56.782834+00:00","Mercado Libre","mercado-libre","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/41cb36b1-2c1a-4b2c-b5d3-315e17d1bdaf.png","RANGE_10000_PLUS",[54],[57],[121,122,123,124],"Google BigQuery","Python","PyTorch","SQL",[126],{"_17":54,"_62":63,"_64":65,"_66":67,"_68":69,"_70":71},[128,129,130,131,132,133,134,135],"Demonstrated command of the full training, evaluation, and inference lifecycle for Computer Vision and NLP models.","Experience optimizing and serving low-latency models with PyTorch, HuggingFace, ONNX, and high-performance inference engines such as vLLM or Llama.cpp.","Practical experience with LLM solution lifecycles, including advanced Context Engineering, RAG, and systematic Prompt Iteration or Prompt Learning.","Experience developing and orchestrating complex agentic workflows with LangChain, LangGraph, or the Google SDK.","Experience configuring and analyzing LLM evaluation metrics with frameworks such as LangSmith, Ragas, or equivalent tools.","Knowledge of efficient fine-tuning techniques such as QLoRA for adapting foundation models to business use cases.","Advanced Python proficiency with software engineering practices including Clean Architecture, automated testing, and CI/CD pipelines.","Experience building large-scale data pipelines with BigQuery and advanced SQL for training and evaluation datasets.",[137,138,139,140,141,142],"Design and evolve low-latency inference solutions for Computer Vision and NLP models in production, optimizing throughput, resource consumption, and response times.","Manage the lifecycle of LLMs and VLMs from exploration and context engineering through production implementation of agentic multimedia workflows.","Build rigorous, reproducible evaluation pipelines to measure changes in models, prompts, and workflows while mitigating regressions and hallucinations.","Apply data-driven prompt learning and continuous iteration to improve solution recall and precision.","Lead architectural design and define clear components and contracts using Spec Driven Development before implementation.","Develop large-scale data pipelines supporting model training, fine-tuning, and continuous evaluation.",[144,145],"Hybrid work arrangement.","Work location at the Bogotá, Colombia site.","https://www.mercadolibre.com/fund",{"_17":148,"_19":20,"_21":149,"_23":150,"_25":151,"_27":152,"_29":-5,"_30":-5,"_31":153,"_34":154,"_36":155,"_38":156,"_39":-5,"_40":157,"_42":158,"_44":159,"_46":47,"_48":160,"_49":50,"_51":-5,"_52":161,"_55":162,"_58":163,"_59":171,"_72":173,"_74":182,"_76":191,"_78":-5,"_79":-5,"_80":-5,"_81":-5,"_82":83,"_84":198,"_85":7,"_86":199},"b91ed13e-3ef3-4bc7-ad77-3ebe1121b124","https://job-boards.greenhouse.io/gofundme/jobs/8040117","Want to help us help others? We’re hiring!\nGoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.\nJoin us! The GoFundMe team is searching for our next Senior Machine Learning Engineer to help design and implement our next generation of machine learning solutions powering search and retrieval, recommendation, and personalization systems. You will collaborate with an accomplished and motivated team of individuals to deliver high-impact solutions for our users and our business.\nCandidates considered for this role will be located in Buenos Aires. There will be an in-office requirement of 3x a week.\nThe Job…\n<ul>\n<li>Design and implement AI/ML systems across personalization, recommendations, content understanding, fraud detection, next-best-action services, and more, including batch inference pipelines and real-time applications.</li>\n<li>Design and contribute to the development of taxonomy and ontology structures and content understanding, classification, and tagging systems that provide the foundational signals for discovery, personalization, and recommendations across the company.</li>\n<li>Partner with product and platform stakeholders to define and evolve catalogs, taxonomies, and entity understanding that improve discovery, relevance, and user experiences.</li>\n<li>Design and apply graph-based techniques—such as graph databases, knowledge graphs, and graph algorithms/models—to enhance retrieval, recommendations, personalization, and content understanding.</li>\n<li>Develop and deploy robust, fault tolerant, high-throughput services, emphasizing reliability, scalability, observability, and low-latency performance.</li>\n<li>Lead initiatives to optimize the performance and quality of ML systems using new or established offline and online metrics (e.g., relevance, ranking quality, coverage/diversity, engagement, and long-term user value).</li>\n<li>Support operational excellence by participating in initiatives to streamline ML workflows and establish standardized procedures to ensure consistent and high-quality outcomes across our projects and systems.</li>\n<li>Collaborate closely with AI/ML engineers and cross-functional teams, including data scientists, software engineers, product managers, and business stakeholders, to foster a culture of collaboration, scientific inquiry, and continuous learning.</li>\n<li>Employ a diverse set of tools and platforms, including Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, and GitHub, to develop, deploy, and maintain scalable and robust machine learning systems.</li>\n</ul>\nYou…\n<ul>\n<li>4+ years of hands-on experience in machine learning, applied ML engineering, data science, or related fields, with a strong emphasis on practical engineering applications and deploying robust solutions into production environments.</li>\n<li>Extensive experience with one or more of the following: search and retrieval systems (including ranking and relevance), recommendation systems, and personalization systems; experience combining these capabilities into end-to-end discovery experiences is a plus.</li>\n<li>Experience designing, developing, and deploying end-to-end ML systems, including data pipelines, feature engineering, model training and serving, and monitoring solutions.</li>\n<li>Experience with catalogs, taxonomies, entity resolution, embeddings, and/or semantic representations used to improve retrieval and recommendation quality.</li>\n<li>Familiarity with graph databases and knowledge graphs (e.g., modeling entities/relationships, building graph-powered features, applying graph algorithms, and/or graph ML) to support retrieval, recommendation, and personalization use cases.</li>\n<li>Demonstrated ability to guide projects and foster a collaborative and high-performing work environment that values continuous improvement and knowledge sharing.</li>\n<li>Ability to break down complex projects, effectively scope and sequence work, and manage timelines to ensure the timely and successful delivery of machine learning initiatives.</li>\n<li>Excellent verbal and written communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.</li>\n<li>Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, Data Science, or a related technical field is preferred.</li>\n<li>A sense of humor is optional but appreciated.</li>\n</ul>\nWhy you’ll love it here...\n<ul>\n<li>Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year.</li>\n<li>Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere.</li>\n<li>Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together.</li>\n<li>Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits.</li>\n<li>Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, and commuting, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being.</li>\n<li>Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow.</li>\n<li>Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups.</li>\n<li>Community Engagement: Make a difference through our volunteering and Gives Back programs.</li>\n</ul>\nWe live by our core values: impatient to be great, find a way, earn trust every day, fueled by purpose. Be a part of something bigger with us!\nGoFundMe is proud to be an equal opportunity employer that actively pursues candidates of diverse backgrounds and experiences. We are committed to providing diversity, equity, and inclusion training to all employees, and we do not discriminate on the basis of race, color, religion, ethnicity, nationality or national origin, sex, sexual orientation, gender, gender identity or expression, pregnancy status, marital status, age, medical condition, mental or physical disability, or military or veteran status.\nIf you require a reasonable accommodation to complete a job application or a job interview or to otherwise participate in the hiring process, please contact us at accommodationrequests@gofundme.com. \nGlobal Data Privacy Notice for Job Candidates and Applicants:\nDepending on your location, the General Data Protection Regulation (GDPR) or certain US privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available <a href="https://www.gofundme.com/c/personal-privacy-notice-for-classy-and-gofundme">here</a>. By submitting your application, you are agreeing to our use and processing of your data as required. \nLearn more about GoFundMe:\nWe’re proud to partner with <a href="https://www.gofundme.org/">GoFundMe.org</a>, an independent public charity, to extend the reach and impact of our generous community, while helping drive critical social change. You can learn more about GoFundMe.org’s activities and impact in their <a href="https://www.gofundme.org/wp-content/uploads/2024/08/GoFundMe.org-FY24-Annual-Report.pdf">FY ‘24 annual report</a>.\nOur<a href="https://www.gofundme.com/c/gofundme-2024-year-in-help"> annual “Year in Help” report </a>reflects our community’s impact in advancing our mission of helping people help each other.\nFor recent company news and announcements, visit our <a href="https://www.gofundme.com/c/newsroom">Newsroom</a>.","Build and scale machine learning systems powering GoFundMe’s search, recommendations, personalization, fraud detection, and content understanding experiences. This Buenos Aires-based role combines end-to-end ML engineering with graph-based discovery and production service development.","GoFundMe is seeking a Senior Machine Learning Engineer to build production machine learning systems for search, retrieval, recommendations, personalization, fraud detection, and content understanding. The role covers end-to-end ML engineering, including data pipelines, feature engineering, model training and serving, batch inference, real-time applications, monitoring, and performance optimization. The engineer will also work with taxonomies, ontologies, entity understanding, graph databases, knowledge graphs, and graph-based techniques to improve discovery and relevance. Candidates should have at least four years of practical ML or related experience, strong production deployment experience, and familiarity with the listed cloud, data, containerization, and development tools. The position is based in Buenos Aires and requires working in the office three times per week.",[33],"2026-07-28T20:51:53+00:00","2026-07-28T22:19:58.497425+00:00","2026-09-04T22:44:22.536652+00:00","GoFundMe","gofundme","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/7708a431-43cb-4d1f-9f59-2afcd0367e79.jpg",true,[54],[57],[164,165,166,167,168,122,169,170],"AWS","Databricks","Docker","FastAPI","Kubernetes","Snowflake","Terraform",[172],{"_17":54,"_62":63,"_64":65,"_66":67,"_68":69,"_70":71},[174,175,176,177,178,179,180,181],"At least four years of hands-on experience in machine learning, applied ML engineering, data science, or a related field.","Extensive experience with search and retrieval, recommendation, or personalization systems; combined end-to-end discovery experience is a plus.","Experience designing, developing, and deploying end-to-end ML systems involving data pipelines, feature engineering, model training and serving, and monitoring.","Experience with catalogs, taxonomies, entity resolution, embeddings, or semantic representations.","Familiarity with graph databases, knowledge graphs, graph algorithms, or graph machine learning.","Ability to guide projects, scope and sequence complex work, manage timelines, and foster collaborative, high-performing teams.","Excellent verbal and written communication skills for technical and non-technical audiences.","A Master’s or Ph.D. in Computer Science, Statistics, Data Science, or a related technical field is preferred.",[183,184,185,186,187,188,189,190],"Design and implement ML systems for personalization, recommendations, content understanding, fraud detection, next-best-action services, and related applications.","Develop taxonomy, ontology, classification, tagging, catalog, and entity-understanding systems that support discovery and recommendations.","Apply graph databases, knowledge graphs, and graph algorithms or models to retrieval, recommendation, personalization, and content understanding.","Build and deploy fault-tolerant, high-throughput, observable, scalable, and low-latency ML services and applications.","Optimize ML system performance and quality using offline and online metrics such as relevance, ranking quality, coverage, diversity, engagement, and long-term user value.","Establish standardized ML workflows and operational procedures to support reliable, consistent outcomes.","Collaborate with AI/ML engineers, data scientists, software engineers, product managers, and business stakeholders.","Use Python, AWS, Databricks, Docker, Kubernetes, FastAPI, Terraform, Snowflake, and GitHub to develop, deploy, and maintain ML systems.",[192,193,194,195,196,197],"Buenos Aires-based role with an in-office requirement three times per week.","Competitive pay and comprehensive healthcare benefits.","Financial assistance for hybrid work, family planning, and commuting.","Generous parental leave, flexible time-off policies, and mental health and wellness resources.","Learning, development, recognition, volunteering, and Gives Back programs.","Diversity, equity, and inclusion initiatives and employee resource groups.",48,"http://www.gofundme.com",{"_17":201,"_19":202,"_21":203,"_23":204,"_25":205,"_27":206,"_29":-5,"_30":-5,"_31":207,"_34":208,"_36":209,"_38":210,"_39":-5,"_40":211,"_42":212,"_44":213,"_46":47,"_48":160,"_49":214,"_51":215,"_52":216,"_55":217,"_58":220,"_59":224,"_72":226,"_74":234,"_76":244,"_78":-5,"_79":-5,"_80":-5,"_81":-5,"_82":83,"_84":247,"_85":7,"_86":248},"26b19c09-5251-4f19-8e6c-dce19ccd9283","AI Systems Engineer","https://job-boards.greenhouse.io/dialpad/jobs/8631737002","<div class="content-intro">About Dialpad Dialpad is the AI-native business communications platform. We unify calling, messaging, meetings, and contact center on a single platform - powered by AI that understands every conversation in real time.\nMore than 70,000 companies around the globe, including WeWork, Asana, NASDAQ, AAA Insurance, COMPASS Realty, Uber, Randstad, and Tractor Supply, rely on Dialpad to build stronger customer connections using real-time, AI-driven insights.\nWe’re now leading the shift to Agentic AI: intelligent agents that don’t just analyze conversations but take action by automating workflows, resolving customer issues, and accelerating revenue in real time. Our DAART initiative (Dialpad Agentic AI in Real Time) is redefining what a communications platform can do.\nVisit <a href="https://dialpad.com/">dialpad.com</a> to learn more.\nBeing a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more.\nWe believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves.\nWe look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic.</div>Your role We are hiring AI Inference Platform Engineers to build the production systems that serve our in-house AI models at scale.\nThis role sits at the intersection of model development, high-performance runtime systems, and cloud infrastructure. You will help turn trained models and emerging AI capabilities into reliable, observable, low-latency production services running on NVIDIA GPUs in GCP.\nThis is not a research role, and it is not a generic MLOps or support role. It is an implementation-heavy systems engineering role focused on the machinery of inference: model serving, runtime optimization, GPU utilization, deployment safety, traffic management, benchmarking, and production reliability.\nOur mission is to shorten the path from promising model capability to dependable production impact. We build the shared infrastructure, standards, and release pathways that allow models to move from candidate artifacts into scalable, rollback-safe inference services with clear performance, reliability, and cost characteristics.\nThis is a new team, so the systems and interfaces are still being shaped. You will help define how models are packaged, deployed, benchmarked, monitored, compared, and operated across environments. The work is practical, deeply technical, and closely tied to the company’s broader AI strategy. We are not building one-off demos; we are building the inference platform by which a growing AI organization can repeatedly and safely ship real model-backed products.\nWhat you’ll do\n<ul>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">You will design, build, and improve the systems that connect AI capability development to production inference.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Depending on your strengths, your work may include:</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Inference Serving & Runtime Systems: Build and improve model-serving pathways for low-latency, high-throughput, high-availability inference workloads.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">GPU Infrastructure & Utilization: Operate and optimize containerized workloads on Kubernetes/GCP, with a focus on efficient use of NVIDIA GPUs, memory, storage, and networking.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Model Server Integration: Work with model-serving frameworks and runtimes such as vLLM, Triton, TGI, or similar systems, adapting them to internal deployment, observability, and release requirements.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Traffic & Release Safety: Enable shadow serving, canary rollouts, staged deployments, candidate-versus-incumbent comparisons, and fast rollback mechanisms for model-backed services.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Benchmarking & Evaluation Infrastructure: Build tooling to measure latency, throughput, cost, saturation behavior, and reliability under realistic production traffic.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Artifact Lifecycle: Improve how model and capability artifacts are packaged, versioned, promoted, deployed, and rolled back across environments.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Observability & Debuggability: Strengthen runtime telemetry, structured logging, tracing, dashboards, and alerting so engineers can understand model-serving behavior in production.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Efficiency & Scale: Contribute to strategies that improve compute efficiency, GPU utilization, autoscaling behavior, and cost-performance tradeoffs across the inference platform.</li>\n</ul>\nSkills you’ll bring\n<ul>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Production Engineering Experience: 6+ years of professional software engineering experience, with a track record of shipping backend services, infrastructure systems, or production platforms that matter.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Strong Software Fundamentals: Proficiency in writing maintainable production code in Python, Go, or another backend-oriented language, with strong debugging and systems-thinking skills.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Inference or Systems Orientation: Experience building, operating, or optimizing high-throughput services, distributed systems, data/ML infrastructure, or runtime platforms where latency, reliability, and resource utilization matter.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Kubernetes & Linux Fluency: Hands-on experience with containers, Kubernetes, Linux environments, CI/CD, deployment automation, and production operations.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Operational Judgment: A strong instinct for reproducibility, observability, rollout safety, failure modes, and whole-system resilience.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Performance Awareness: Comfort reasoning about bottlenecks across compute, memory, network, storage, batching, concurrency, and service-level objectives.</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Collaboration: Ability to work closely with model developers, product engineers, infrastructure teams, and technical leadership to turn evolving AI capabilities into reliable production systems.</li>\n</ul><div class="content-conclusion">Why Join Dialpad\n<ul>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Work at the center of the AI transformation in business communications</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Build and ship agentic AI products that are redefining how companies operate</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Join a team where AI amplifies every employee’s impact</li>\n<li style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">Competitive salary, comprehensive benefits, and real opportunities for growth</li>\n</ul>\nWe believe in investing in our people. Dialpad offers competitive benefits and perks, cutting-edge AI tools, and a robust training program that help you reach your full potential. We have designed our offices to be inclusive, offering a vibrant environment to cultivate collaboration and connection. Our exceptional culture, repeatedly recognized as a <a href="https://www.greatplacetowork.com/certified-company/7007999#:~:text=91%25%20of%20employees%20at%20Dialpad,a%20typical%20U.S.-based%20company.&text=Source:%20Great%20Place%20To%20Work%C2%AE%202021%20Global%20Employee%20Engagement%20Study.&text=When%20you%20join%20the%20company,%20you%20are%20made%20to%20feel%20welcome.&text=People%20here%20are%20given%20a%20lot%20of%20responsibility">Great Place to Work</a>, ensures that every employee feels valued and empowered to contribute to our collective success.\nDon’t meet every single requirement? If you’re excited about this role and possess the fundamental traits, drive, and strong ambition we seek, but your experience doesn’t meet every qualification, we encourage you to apply. \n Dialpad is an equal-opportunity employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment.</div>","Build the production inference platform that turns Dialpad’s AI models into reliable, low-latency services running on NVIDIA GPUs in GCP. You’ll work across model serving, runtime optimization, deployment safety, benchmarking, observability, and platform scalability.","Dialpad is hiring an AI Inference Platform Engineer to build production systems that serve in-house AI models at scale. The role focuses on model serving, runtime optimization, NVIDIA GPU utilization, deployment safety, traffic management, benchmarking, observability, and production reliability in GCP. Responsibilities include integrating model-serving frameworks, enabling canary and shadow deployments, managing model artifacts, and improving performance, autoscaling, and cost efficiency. Candidates need 6+ years of professional software engineering experience, backend or infrastructure expertise, and hands-on experience with Kubernetes, Linux, containers, deployment automation, and production operations. This is an implementation-heavy systems engineering role on a new team shaping the shared inference platform rather than a research or generic MLOps position.",[33],"2026-07-13T20:11:15+00:00","2026-07-13T20:19:24.537016+00:00","2026-09-04T22:35:00.219334+00:00","Dialpad","dialpad","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/48d79f14-90fc-4f4b-a04f-4f34fa8d6549.jpg","RANGE_1001_5000","SERIES_E_PLUS",[54],[218,219,57],"Backend","DevOps",[221,222,168,223,122],"Go","Google Cloud Platform","Linux",[225],{"_17":54,"_62":63,"_64":65,"_66":67,"_68":69,"_70":71},[227,228,229,230,231,232,233],"6+ years of professional software engineering experience shipping backend services, infrastructure systems, or production platforms.","Proficiency in Python, Go, or another backend-oriented programming language, with strong debugging and systems-thinking skills.","Experience building, operating, or optimizing high-throughput services, distributed systems, data or ML infrastructure, or runtime platforms.","Hands-on experience with containers, Kubernetes, Linux environments, deployment automation, and production operations.","Ability to reason about compute, memory, networking, storage, batching, concurrency, latency, reliability, and service-level objectives.","Strong judgment around reproducibility, observability, rollout safety, failure modes, and whole-system resilience.","Ability to collaborate with model developers, product engineers, infrastructure teams, and technical leadership.",[235,236,237,238,239,240,241,242,243],"Design, build, and improve systems connecting AI capability development to production inference.","Build and optimize low-latency, high-throughput, high-availability model-serving and runtime systems.","Operate and optimize containerized Kubernetes workloads in GCP, including efficient NVIDIA GPU, memory, storage, and networking utilization.","Integrate model-serving frameworks such as vLLM, Triton, and TGI with internal deployment, observability, and release requirements.","Enable shadow serving, canary rollouts, staged deployments, candidate-versus-incumbent comparisons, and fast rollback mechanisms.","Build benchmarking and evaluation tools for latency, throughput, cost, saturation behavior, and reliability under realistic production traffic.","Improve packaging, versioning, promotion, deployment, and rollback processes for model and capability artifacts.","Strengthen runtime telemetry, structured logging, tracing, dashboards, and alerting for production model-serving systems.","Improve compute efficiency, GPU utilization, autoscaling behavior, and cost-performance tradeoffs across the inference platform.",[245,246],"Competitive benefits and perks, including a robust training program and AI tools.","Inclusive office environment designed to support collaboration and connection.",72,"https://www.dialpad.com",{"_17":250,"_19":251,"_21":252,"_23":253,"_25":254,"_27":255,"_29":-5,"_30":-5,"_31":256,"_34":257,"_36":258,"_38":259,"_39":-5,"_40":260,"_42":261,"_44":262,"_46":47,"_48":160,"_49":263,"_51":215,"_52":264,"_55":265,"_58":267,"_59":275,"_72":277,"_74":285,"_76":294,"_78":-5,"_79":-5,"_80":-5,"_81":-5,"_82":83,"_84":247,"_85":7,"_86":295},"28e2cc75-79c0-4367-a962-6b9467f83152","Software Engineer","https://job-boards.greenhouse.io/scaleai/jobs/4612282005","Software Engineer - Robotics & Autonomous Systems\nScale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems.\nYou Will:\n<ul>\n<li>Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets</li>\n<li>Build ML training and fine-tuning pipelines using Scale's robotics data</li>\n<li>Work across backend (Python, <a href="http://node.js">Node.js</a>, C++) and frontend (React, TypeScript) stacks to build end-to-end solutions</li>\n<li>Develop tools and systems for robotics data collection, teleoperation, and model evaluation</li>\n<li>Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development</li>\n<li>Build real-time systems for robotic control, sensor fusion, and perception pipelines</li>\n<li>Design comprehensive monitoring and evaluation frameworks for robotics models and data quality</li>\n<li>Collaborate with ML engineers and researchers to bring robotics research into production</li>\n<li>Deliver features at high velocity while maintaining system reliability and performance</li>\n</ul>\nIdeally, You Have:\n<ul>\n<li>3+ years of software engineering experience in robotics, autonomous vehicles, or related fields and at least 6 years of experience in software engineering.</li>\n<li>Strong programming skills in Python and TypeScript/Node.js for production systems</li>\n<li>Experience with React and modern frontend development for 3D interfaces</li>\n<li>Practical experience with robotics frameworks (ROS/ROS2), simulation environments, or AV systems</li>\n<li>Understanding of distributed systems, workflow orchestration, and cloud infrastructure (AWS, Temporal, Kubernetes, Docker)</li>\n<li>Experience with databases (MongoDB, PostgreSQL) and data processing at scale</li>\n<li>Track record of working with cross-functional teams including ML engineers, researchers, and customers</li>\n<li>Strong communication skills and ability to operate with high autonomy</li>\n</ul>\nNice to Haves:\n<ul>\n<li>Experience with C++</li>\n<li>Experience with robotics hardware platforms (robotic arms, mobile robots, perception systems) with a focus on time synchronization</li>\n<li>Background in computer vision, SLAM, motion planning, or imitation learning</li>\n<li>Familiarity with autonomous vehicle data, lidar technologies, or 3D data processing</li>\n<li>Experience with ML model deployment and serving frameworks</li>\n<li>Knowledge of teleoperation systems (ALOHA, UMI, hand tracking) or VR interfaces</li>\n<li>Experience with workflow orchestration systems (Temporal, Airflow)</li>\n<li>Published research or open-source contributions in robotics or autonomous systems</li>\n</ul><div class="content-conclusion">PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.\nAbout Us:\nAt Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.\nWe believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. \nWe are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's <a href="https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf">Know Your Rights poster</a> for additional information.\nWe comply with the United States Department of Labor's <a href="https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_English_unformattedESQA508c.pdf">Pay Transparency provision</a>. \nPLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our <a href="https://scale.com/legal/privacy" target="_blank">privacy policy</a> for additional information.</div>","Build end-to-end robotics and autonomous systems software spanning data pipelines, ML training, evaluation infrastructure, and real-time robotic systems. You’ll work directly with robotics customers and cross-functional ML and research teams to productionize embodied AI capabilities.","The Software Engineer will build production systems for robotics data collection, model training, evaluation, and embodied AI platforms. Responsibilities span large-scale data processing, backend and frontend development, real-time robotic control, sensor fusion, perception, and monitoring systems. The role requires at least six years of software engineering experience, including three or more years in robotics, autonomous vehicles, or related fields. Candidates should have strong Python and TypeScript/Node.js skills, experience with robotics frameworks and cloud infrastructure, and familiarity with distributed systems and databases. The position is customer-facing and collaborative, working with robotics stakeholders, ML engineers, researchers, and AV teams to bring research into production.",[33],"2025-12-30T14:08:20+00:00","2025-12-30T14:15:22.823521+00:00","2026-09-04T22:35:08.146991+00:00","Scale AI","scale-ai","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/9cb6d554-8093-4fa4-ac02-c7ef7cdd0000.jpg","RANGE_501_1000",[54],[218,57,266],"Robotics",[268,164,269,166,168,270,271,272,122,273,274],"Apache Airflow","C++","MongoDB","Node.js","PostgreSQL","React","TypeScript",[276],{"_17":54,"_62":63,"_64":65,"_66":67,"_68":69,"_70":71},[278,279,280,281,282,283,284],"At least 6 years of software engineering experience, including 3 or more years in robotics, autonomous vehicles, or related fields.","Strong production programming skills in Python and TypeScript/Node.js, with experience using React for modern frontend and 3D interfaces.","Practical experience with robotics frameworks such as ROS or ROS2, simulation environments, or autonomous vehicle systems.","Experience with distributed systems, workflow orchestration, cloud infrastructure, databases, and large-scale data processing.","Experience collaborating with ML engineers, researchers, customers, and cross-functional stakeholders.","Experience with C++, robotics hardware, computer vision, SLAM, motion planning, imitation learning, lidar, 3D data processing, ML model serving, or teleoperation is desirable.","Published research or open-source contributions in robotics or autonomous systems are desirable.",[286,287,288,289,290,291,292,293],"Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets.","Build ML training and fine-tuning pipelines using robotics data.","Develop end-to-end backend and frontend systems using Python, Node.js, C++, React, and TypeScript.","Build tools for robotics data collection, teleoperation, model evaluation, and data-quality monitoring.","Develop real-time systems for robotic control, sensor fusion, and perception pipelines.","Design monitoring and evaluation frameworks for robotics models and data quality.","Work directly with robotics and autonomous vehicle stakeholders and collaborate with ML engineers and researchers to bring robotics research into production.","Deliver reliable, high-performance features at high velocity.",[],"https://scale.com",{"_17":297,"_19":298,"_21":299,"_23":300,"_25":301,"_27":302,"_29":-5,"_30":-5,"_31":303,"_34":304,"_36":305,"_38":305,"_39":-5,"_40":306,"_42":307,"_44":308,"_46":47,"_48":7,"_49":309,"_51":-5,"_52":310,"_55":311,"_58":312,"_59":323,"_72":325,"_74":335,"_76":344,"_78":-5,"_79":-5,"_80":-5,"_81":-5,"_82":83,"_84":-5,"_85":7,"_86":354},"95891401-2904-4aec-899e-5c29c321d61c","Machine Learning Engineer Senior","https://jobs.lever.co/muttdata/8d40f420-1d29-4e94-a87a-6a271ebe3937","# Description\n\n🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀\n \nMutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.\n \nWe’re looking for a Machine Learning Engineer to help take our expertise to the next level. If you consider yourself a data nerd like us, we’d love to connect! 🐶🚀\n\n# Lists\n\n## 🚀 What We Do\n\n

Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.

Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.

Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.

Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.

Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.

Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

\n\n## 🌟 Our Partnerships\n\n

Amazon Web Services

Astronomer

Databricks

\n\n## 🌟 Our Values\n\n

📊 We are Data Nerds

🤗 We are Open Team Players

🚀 We Take Ownership

🌟 We Have a Positive Mindset

\n\n

🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀

\n\n## Responsibilities 🤓\n\n

Develop and optimize ML models, ensuring scalability, monitoring, and integration with MLOps best practices.

Implement client requirements, from exploratory data analysis (EDA) to feature engineering and model lifecycle management.

Build ML Proof of Concepts (POCs) to validate and refine solutions.

Optimize models for performance, latency, memory, and throughput.

Apply statistical analysis techniques and develop regression models.

Design and maintain feature stores and data pipelines for ML workflows.

Research and implement emerging ML/AI techniques to enhance solutions.

Collaborate with stakeholders to align technical solutions with business needs.

\n\n## Required Skills\n\n

Experience implementing ML-based systems, including model lifecycle management, monitoring, and MLOps pipeline setup.

Strong proficiency in Python (Pandas, Numpy, Jupyter, Scikit-Learn, XGBoost, Plotly).Knowledge of SQL

Experience with cloud platforms (AWS, GCP, Azure).

\n\n## Nice to Have Skills 😉\n\n

Experience with ML workflows (Airflow, MLflow, H2OAI, Databricks, or similar).

Background in modern LLM technologies.

Understanding of Deep Learning frameworks (Keras, PyTorch, TensorFlow).Basic knowledge of Docker.

Databricks (Workflows, Jobs, Repos).

\n\n

\n\n## 🎁 Perks\n\n

🌍 Remote-first culture – work from anywhere!

🚀 In-Company English Lessons.

💪 Wellhub or sports club stipend to stay active

🚀 AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered

🍕 Food credits via Pedidos Ya – because great work deserves great food.

🎂 Birthday off + an extra vacation week (Mutt Week! 🏖️)

🤝 Referral bonuses – help us grow the team & get rewarded!

✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!

👶 Monthly Childcare Reimbursement – Because supporting families matters too

","Mutt Data is seeking a Senior Machine Learning Engineer to build scalable ML systems, models, and data workflows for forecasting, recommendations, computer vision, and generative AI solutions. This remote role combines hands-on modeling, MLOps, feature engineering, and client-focused solution development.","The engineer will develop, optimize, monitor, and integrate machine learning models across their full lifecycle, from exploratory data analysis and feature engineering through deployment and maintenance. Responsibilities include building proof-of-concepts, regression models, feature stores, and ML data pipelines while optimizing performance, latency, memory, and throughput. The role requires Python and related data science libraries, SQL, and experience with cloud platforms such as AWS, GCP, and Azure. Familiarity with Airflow, MLflow, H2O.ai, Databricks, LLM technologies, deep learning frameworks, and Docker is preferred. The position is distinguished by its remote-first environment and work across demand planning, forecasting, recommendations, visual recognition, information retrieval, and generative AI applications.",[33],"2023-06-15T15:14:25.676+00:00","2026-09-05T10:18:18.821291+00:00","Muttdata","muttdata","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/b64d0346-ebb9-482b-bb96-9ac73a816ffb.png","RANGE_51_200",[54],[57],[268,164,313,165,314,166,222,315,316,317,318,319,122,123,320,124,321,322],"Azure","dbt","H2O.ai","Keras","MLflow","NumPy","Pandas","scikit-learn","TensorFlow","XGBoost",[324],{"_17":54,"_62":63,"_64":65,"_66":67,"_68":69,"_70":71},[326,327,328,329,330,331,332,333,334],"Experience implementing ML-based systems, including model lifecycle management, monitoring, and MLOps pipeline setup.","Strong proficiency in Python, Pandas, NumPy, Jupyter, Scikit-learn, XGBoost, and Plotly.","Knowledge of SQL.","Experience with AWS, GCP, or Azure.","Preferred experience with Airflow, MLflow, H2O.ai, Databricks, or similar ML workflows.","Preferred background in modern LLM technologies.","Preferred understanding of Keras, PyTorch, or TensorFlow.","Basic knowledge of Docker is preferred.","Databricks experience with Workflows, Jobs, and Repos is preferred.",[336,337,338,339,340,341,342,343],"Develop, optimize, monitor, and integrate scalable machine learning models using MLOps best practices.","Implement client requirements from exploratory data analysis and feature engineering through model lifecycle management.","Build machine learning proof-of-concepts to validate and refine solutions.","Optimize models for performance, latency, memory usage, and throughput.","Apply statistical analysis techniques and develop regression models.","Design and maintain feature stores and data pipelines for machine learning workflows.","Research and implement emerging machine learning and AI techniques.","Collaborate with stakeholders to align technical solutions with business needs.",[345,346,347,348,349,350,351,352,353],"Remote-first culture with the ability to work from anywhere.","In-company English lessons.","Wellhub or sports club stipend.","AWS, dbt, Google Cloud, Azure, and Databricks certifications fully covered.","Food credits through Pedidos Ya.","Birthday off and an additional vacation week.","Referral bonuses.","Annual team trip.","Monthly childcare reimbursement.","https://muttdata.ai","actionData","errors"]

Senior Machine Learning Engineer

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