[{"_1":2,"_380":-5,"_381":-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,"_92":43,"_93":94,"_98":-5,"_99":100},"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":-5,"_50":-5,"_51":52,"_54":55,"_57":-5,"_58":59,"_69":70,"_71":72,"_74":75,"_76":-5,"_77":-5,"_78":-5,"_79":-5,"_80":81,"_82":-5,"_83":7,"_84":85,"_86":7,"_87":88,"_89":-5,"_90":91},"id","ca7aa212-35d5-402b-af4b-8e12253ea1bb","title","Software Engineer","url","https://jobs.ashbyhq.com/clera/80b111f8-2cb3-4804-b45a-e0674d895152","job_description_full","ABOUT THE ROLE\n\nJoin an AI/ML team building technology that transforms raw sensor data into queryable spatial understanding. The platform supports applications across robotics, public safety, construction, and infrastructure inspection.","job_description_summary_short","Join an AI/ML team building technology that transforms raw sensor data into queryable spatial understanding. The platform supports applications in robotics, public safety, construction, and infrastructure inspection.","job_description_summary_long","The Software Engineer will join an AI/ML team developing technology that converts raw sensor data into queryable spatial understanding. The resulting platform supports applications across robotics, public safety, construction, and infrastructure inspection. The posting does not provide specific responsibilities beyond building this technology. It also does not state education, experience, technology, compensation, benefits, or work authorization requirements.","employment_type","compensation","seniority",[33],"entry level","date_posted","2026-10-29T02:45:47.581+00:00","created_at","2026-10-29T04:03:38.783109+00:00","updated_at","deleted_at","company","Clera","company_slug","clera","profile_pic_url","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/215a6b77-0a58-42e6-a97f-1d49fa65d966.png","career_category","Software Engineering","sponsors_h1b","headcount_range","latest_funding_class","location_ids",[53],47984,"sub_categories",[56],"ML Engineering","tech_stack","locations",[60],{"_17":53,"_61":62,"_63":64,"_65":-5,"_66":67,"_68":-5},"city","Remote","slug","remote-worldwide","state","country","Worldwide","country_iso3","requirements",[],"responsibilities",[73],"Build technology that transforms raw sensor data into queryable spatial understanding.","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://clearai.com.au","company_sponsors_h1b","h1b_sponsorship_status","unknown","h1b_sponsorship_evidence","company_id","215a6b77-0a58-42e6-a97f-1d49fa65d966","companySlug","companyInfo",{"_17":91,"_95":41,"_63":43,"_84":85,"_96":-5,"_49":-5,"_97":-5},"name","linkedin_slug","description","h1bHistory","similarJobs",[101,161,209,241,268,328],{"_17":102,"_19":103,"_21":104,"_23":105,"_25":106,"_27":107,"_29":-5,"_30":-5,"_31":108,"_34":109,"_36":110,"_38":110,"_39":-5,"_40":111,"_42":112,"_44":113,"_46":47,"_48":114,"_49":115,"_50":116,"_51":117,"_54":119,"_57":120,"_58":123,"_69":128,"_71":139,"_74":149,"_76":154,"_77":155,"_78":156,"_79":157,"_80":158,"_82":159,"_83":7,"_84":160},"62cf43d9-7ee2-4357-9b2b-33b2af11d53f","AI/ML Engineer","https://caci.wd1.myworkdayjobs.com/External/job/Remote-Any-State/AI-ML-Engineer_334295","Job Title: AI/ML Engineer

Job Category: Science

Time Type: Full time

Minimum Clearance Required to Start: Secret

Employee Type: Regular

Percentage of Travel Required: Up to 10%

Type of Travel: Continental US

* * *

The Opportunity:

CACI is seeking an AI/ML Engineer (Data Scientist T-1) to support superintelligence efforts at the Portsmouth Naval Shipyard (PNS) in Kittery, ME.

The AI/ML Engineer (Data Scientist T-1) supports the development, training, testing, and deployment of machine learning and superintelligence solutions for Portsmouth Naval Shipyard (PNS) and NAVSEA customers. This role works alongside engineers, developers, and divisional teams to develop data-driven solutions that improve mission effectiveness and operational decision-making.
The ideal candidate has experience with AI/ML development, Python programming, Palantir Foundry, and working within secure government environments. This position requires collaboration with cross-functional teams and adherence to customer security, safety, and engineering requirements.

Responsibilities:

• Develop, train, test, and deploy AI/ML models to support customer requirements.
• Support data preparation, feature engineering, model evaluation, and performance optimization activities.
• Develop software and machine learning solutions using Python and industry-standard AI/ML frameworks.
• Work with structured and unstructured datasets to build predictive, analytical, and computer vision solutions.
• Support implementation and deployment of AI/ML capabilities within Palantir Foundry, AIM, and DoW GenAI environments.
• Collaborate with engineers, developers, program managers, and customer stakeholders to deliver technical solutions.
• Document technical approaches, model performance, and development activities.
• Present technical findings and recommendations to project teams and customers.
• Follow customer cybersecurity, configuration management, NMCI, and NNPI requirements.
• Comply with all customer-site engineering, safety, and PPE requirements.

Qualifications:

Required:
• Active U.S. Government Security Clearance.
• Bachelor's degree in Data Science, Computer Science, Super Intelligence, Machine Learning, Engineering, Mathematics, or a related technical field.
• 6+ months of professional experience supporting AI/ML, data science, software engineering, or analytics projects.
• Experience developing machine learning models using Python.
• Experience with Palantir Foundry.
• Experience with AIM.
• Experience working within NMCI environments.
• Familiarity with NNPI requirements and working within secure government environments.
• Strong written and verbal communication skills.
• Ability to work independently and within cross-functional teams.

Desired:
• Experience with computer vision applications, including object detection, classification, or image analysis.
• Experience working with DoW GenAI tools and capabilities.
• Familiarity with AWS cloud services.
• Experience deploying machine learning models into operational environments.
• Experience supporting Navy, DoD, or defense-related programs.
Work Environment:
• Work is performed in customer, office, or engineering environments.
• Compliance with customer security, cybersecurity, NMCI, and information-protection requirements is required.
• Personal Protective Equipment (PPE) may be required based on customer site access requirements.
• Must be able to work effectively within a collaborative engineering and program environment.

What You Can Expect:

A culture of integrity.

At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation.

An environment of trust.

CACI values the unique contributions that every employee brings to our company and our customers - every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.

A focus on continuous growth.

Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy.

Pay Range:

There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.

Since this position can be worked in more than one location, the range shown is the national average for the position.

The proposed salary range for this position is:

$58,000-$115,900

CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.

","AI/ML Engineer developing, training, testing, and deploying machine learning solutions for naval shipyard and NAVSEA customers. The role combines Python, Palantir Foundry, secure government environments, and mission-focused data science.","Develops and deploys AI/ML models, predictive solutions, analytical capabilities, and computer vision applications for Portsmouth Naval Shipyard and NAVSEA customers. Responsibilities include data preparation, feature engineering, model evaluation, performance optimization, technical documentation, and presenting findings to project teams and customers. The engineer works with Python, Palantir Foundry, AIM, and DoW GenAI environments while complying with cybersecurity, NMCI, NNPI, configuration management, safety, and PPE requirements. A bachelor's degree in a relevant technical field, an active U.S. government security clearance, and at least six months of relevant professional experience are required. Experience with AWS, operational ML deployment, computer vision, and Navy, DoD, or defense programs is preferred.",[33],"2026-10-28T00:00:00+00:00","2026-10-28T20:54:05.516478+00:00","CACI International","caci-international","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/983b424e-f41a-4e8f-a405-81ce859854b8.jpg",true,"RANGE_10000_PLUS","PUBLIC",[118],47981,[56],[121,122],"AWS","Python",[124],{"_17":118,"_61":62,"_63":125,"_65":-5,"_66":126,"_68":127},"remote-usa","United States","USA",[129,130,131,132,133,134,135,136,137,138],"Active U.S. Government Security Clearance.","Bachelor's degree in Data Science, Computer Science, Super Intelligence, Machine Learning, Engineering, Mathematics, or a related technical field.","At least 6 months of professional experience supporting AI/ML, data science, software engineering, or analytics projects.","Experience developing machine learning models using Python.","Experience with Palantir Foundry and AIM.","Experience working within NMCI environments and familiarity with NNPI requirements and secure government environments.","Strong written and verbal communication skills and the ability to work independently and within cross-functional teams.","Preferred experience with computer vision, including object detection, classification, or image analysis.","Preferred experience with DoW GenAI tools, AWS cloud services, operational ML deployment, or Navy, DoD, or defense-related programs.","Ability to support work in customer, office, or engineering environments and comply with customer security and information-protection requirements.",[140,141,142,143,144,145,146,147,148],"Develop, train, test, and deploy AI/ML models supporting customer requirements.","Prepare data, perform feature engineering and model evaluation, and optimize model performance.","Develop Python-based software and machine learning solutions using industry-standard AI/ML frameworks.","Build predictive, analytical, and computer vision solutions from structured and unstructured datasets.","Implement and deploy AI/ML capabilities in Palantir Foundry, AIM, and DoW GenAI environments.","Collaborate with engineers, developers, program managers, customers, and cross-functional teams.","Document technical approaches, model performance, and development activities.","Present technical findings and recommendations to project teams and customers.","Follow customer cybersecurity, configuration management, NMCI, NNPI, engineering, safety, and PPE requirements.",[150,151,152,153],"Full-time regular employee position with up to 10% travel within the continental United States.","Flexible time off benefit, healthcare, wellness, financial, retirement, family support, continuing education, and other time-off benefits.","Access to learning and development resources and opportunities for continuous career growth.","Work may occur at customer, office, or engineering sites, with PPE required based on customer-site access requirements.",58000,115900,"USD","YEAR","bachelor-degree",6,"http://www.caci.com",{"_17":162,"_19":163,"_21":164,"_23":165,"_25":166,"_27":167,"_29":-5,"_30":-5,"_31":168,"_34":169,"_36":170,"_38":170,"_39":-5,"_40":171,"_42":172,"_44":173,"_46":47,"_48":114,"_49":174,"_50":175,"_51":176,"_54":178,"_57":179,"_58":183,"_69":188,"_71":199,"_74":206,"_76":-5,"_77":-5,"_78":-5,"_79":-5,"_80":158,"_82":207,"_83":7,"_84":208},"17d2865f-90f9-47a2-a6a5-adfca4574afc","Machine Learning Engineer 1","https://abnormal.ai/careers/jobs/8002099003?gh_jid=8002099003","<h3><strong>About the Role</strong></h3>\n<p>Abnormal AI is seeking a Machine Learning Engineer - I (MLE) to join the Misdirected Email Detection (MED) team. The MED team plays a critical role in preventing accidental data loss by detecting and blocking misdirected outbound emails, delivering protection at scale without adding operational burden to customer SOCs.</p>\n<p>This is a highly applied role for MLEs who thrive on building, iterating, and experimenting. Rather than focusing solely on model training, you will also be responsible for developing practical, end-to-end ML solutions. This includes but is not limited to generating and refining features, testing hypotheses, averaging signals, and translating research ideas into production-grade systems, all while collaborating cross-functionally to turn customer needs into measurable product improvements. The ideal candidate combines a tinkerer's mindset with technical rigor, balancing innovation with production excellence to drive experimentation, scale solutions, and deliver reliable detection capabilities that create meaningful customer impact in real-world environments.</p>\n<h3><strong>What you will do</strong></h3>\n<ul>\n<li>Partner with Product Manager, Tech Lead and engineering stakeholders to align technical deliverables to roadmap milestones and ensure successful GA launches across supported environments.</li>\n<li>Own the full ML lifecycle for Misdirected Email, including data wrangling, feature engineering, model training and evaluation, deployment, and monitoring. Deliver iterative improvements with measurable reliability and customer impact.</li>\n<li>Run rigorous experiments and evaluations (offline metrics, online A/B testing, post-launch monitoring), set thresholds, and conduct targeted error analysis to prevent regressions.</li>\n<li>Communicate effectively across time zones, maintain high-quality technical documentation, and contribute to shared team knowledge.</li>\n<li>Participate in shared on-call rotation for owned components, with responsibilities focused on detection efficacy and realtime scoring systems. Priorities include resolving efficacy-related alerts, investigating high-visibility false positives, and addressing reported false positives/false negatives from customers or internal teams.</li>\n</ul>\n<h3><strong>Must Haves</strong></h3>\n<ul>\n<li>BS degree in Computer Science, Machine Learning, Artificial Intelligence, Information Systems, or a related engineering or quantitative field.</li>\n<li>1+ years building and operating applied ML features in production systems.</li>\n<li>Proven experience contributing to end-to-end ML systems, including data wrangling (text and structured), feature engineering, model selection, training, evaluation, and production deployment with monitoring.</li>\n<li>Demonstrated ability to implement and reason about algorithms, develop features, average and combine signals, and apply numerical computing effectively.</li>\n<li>Demonstrated ability to interrogate production data, identify behavioral or trend shifts, and launch targeted experiments to improve model efficacy.</li>\n<li>Understanding of online vs offline pipelines, data tables and labeling workflows to effectively leverage tooling to support safe, scalable model deployments.</li>\n<li>Experience running offline metrics, online A/B tests, setting thresholds, and monitoring drift and performance, with guardrails and rollback strategies to ensure reliable iteration.</li>\n<li>Strong written and asynchronous communication skills. Effective working independently and across distributed, cross-functional teams.</li>\n</ul>\n<h3><strong>Nice to Have</strong></h3>\n<ul>\n<li>Experience with our stack: Python, Go, AWS, Spark, Databricks</li>\n<li>Experience in email security/DLP or misdirected email prevention domains and customer-focused ML deployments.</li>\n<li>Experience writing detectors/rules to complement ML models for safe launches and rapid iteration.</li>\n<li>Experience with operationalising research into reliable, customer-facing systems, with emphasis on scalability, performance, and detection accuracy in real-world environments.</li>\n<li>Prior experience contributing to a small team or project to deliver a feature or component from scratch.</li>\n</ul>\n<p>#LI-UC1</p><div class="content-conclusion"><p><strong>A note on AI in our process: <br></strong>Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards.</p>\n<p>Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please <a href="https://assets.contentstack.io/v3/assets/blt3a076cfd9753fa1f/blt9cbda641db7c0045/6a1e3d3a66aea075cd33e462/AAP_and_EEO_Statement.pdf" target="_blank"><span style="text-decoration: underline;"><em>click here</em></span></a>. If you would like more information on your EEO rights under the law, please <em><span style="text-decoration: underline;"><a href="https://assets.contentstack.io/v3/assets/blt3a076cfd9753fa1f/blt4eb3a265cc7b1ca9/6a1e3d3bfe33e73c16ff026b/EEOC_Know_Your_Rights_Oct_30_2025.pdf" target="_blank">click here</a></span></em>.</p></div>","Abnormal AI is hiring a Machine Learning Engineer I to build and operate end-to-end ML systems for its Misdirected Email Detection team. The role combines feature engineering, experimentation, model deployment, monitoring, and production improvements that reduce accidental data loss.","The engineer will own the full machine learning lifecycle, including data wrangling, feature engineering, model training, evaluation, deployment, and monitoring. They will run offline metrics, online A/B tests, threshold-setting, error analysis, and drift monitoring to improve detection efficacy and prevent regressions. The role includes investigating false positives and false negatives, responding to efficacy-related alerts, and participating in an on-call rotation for real-time scoring systems. Candidates need a bachelor's degree in a relevant technical field and at least one year of experience building and operating applied ML features in production. Experience with Python, Go, AWS, Spark, and Databricks, as well as email security or DLP, is preferred.",[33],"2026-10-27T04:50:30+00:00","2026-10-27T06:03:56.008036+00:00","Abnormal Security","abnormal-security","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/7fd76324-ab93-4e9c-8e2f-81812436ec51.jpg","RANGE_1001_5000","SERIES_D",[177],48016,[56],[180,121,181,182,122],"Apache Spark","Databricks","Go",[184],{"_17":177,"_61":62,"_63":185,"_65":-5,"_66":186,"_68":187},"remote-sgp","Singapore","SGP",[189,190,191,192,193,194,195,196,197,198],"Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Information Systems, or a related engineering or quantitative field.","At least 1 year of experience building and operating applied ML features in production systems.","Experience contributing to end-to-end ML systems, including data wrangling, feature engineering, model selection, training, evaluation, production deployment, and monitoring.","Ability to implement and reason about algorithms, develop features, combine signals, and apply numerical computing effectively.","Experience interrogating production data, identifying behavioral or trend shifts, and running targeted experiments to improve model efficacy.","Understanding of online and offline pipelines, data tables, and labeling workflows for safe and scalable model deployments.","Experience with offline metrics, online A/B tests, threshold-setting, drift and performance monitoring, guardrails, and rollback strategies.","Strong written and asynchronous communication skills and the ability to work independently across distributed, cross-functional teams.","Preferred experience with Python, Go, AWS, Spark, and Databricks.","Preferred experience in email security, data loss prevention, misdirected email prevention, customer-focused ML deployments, detector or rule development, and operationalizing research into reliable customer-facing systems.",[200,201,202,203,204,205],"Partner with product, technical, and engineering stakeholders to align technical deliverables with roadmap milestones and support general-availability launches.","Own the end-to-end ML lifecycle for misdirected email, including data wrangling, feature engineering, model training, evaluation, deployment, and monitoring.","Run offline evaluations, online A/B tests, threshold-setting, targeted error analysis, and post-launch monitoring to improve model efficacy and prevent regressions.","Investigate production data and behavioral or trend shifts, and launch experiments that improve detection reliability and customer impact.","Participate in an on-call rotation for owned components, resolving efficacy-related alerts and investigating customer or internal reports of false positives and false negatives.","Maintain technical documentation and communicate effectively across distributed, cross-functional teams.",[],12,"https://www.abnormalsecurity.com",{"_17":210,"_19":211,"_21":212,"_23":213,"_25":214,"_27":215,"_29":-5,"_30":-5,"_31":216,"_34":217,"_36":218,"_38":218,"_39":-5,"_40":219,"_42":220,"_44":221,"_46":47,"_48":7,"_49":222,"_50":-5,"_51":223,"_54":224,"_57":-5,"_58":225,"_69":227,"_71":231,"_74":236,"_76":-5,"_77":-5,"_78":-5,"_79":-5,"_80":81,"_82":-5,"_83":7,"_84":240},"5d561db7-60b0-4316-9a70-48f85bc2018a","AI Engineer / LLM Engineer - G2i Talent Pool","https://jobs.ashbyhq.com/g2i/a5672c66-5fb8-4d5d-8984-e8c7a9edda1e","Join the G2i Talent Pool\n\nWe’re always meeting great people in tech. Join the G2i Talent Pool and let us get to know you.\n\nG2i works with top AI labs and fast-growing companies. Our community of engineers works on real projects, from evals and RL environments to training data for frontier models.\n\n\n\nWho we’re looking for\nSoftware, data, AI/ML, infrastructure, security, design, QA and product. Experienced or just starting out, fresh graduates are welcome. If you work in tech or are building your career in it, we’d love to meet you.\n\n\n\nHow it works\n\n 1. Apply in a few minutes with your real details and links.\n\n 2. We review your profile and send you a short technical assessment.\n\n 3. Once you pass, you join our pool and hear from us when a project fits your skills.\n\n\n\nJoining the pool doesn’t mean immediate work, since matching depends on what our clients need and on each profile. But we’re always working to match everyone in our pool with the right project.\n\nPlease note that eligibility may vary depending on your location, as some regions may not be supported by the client.","Join G2i’s talent pool for potential AI, software, data, infrastructure, security, design, QA, or product projects with leading AI labs and fast-growing companies. After a short technical assessment, qualified candidates are matched to projects based on their skills and client needs.","G2i is building a talent pool of technology professionals, including AI/ML and LLM engineers, software engineers, data professionals, infrastructure specialists, security professionals, designers, QA professionals, and product contributors. Projects may involve evaluations, reinforcement-learning environments, training data for frontier models, and other client work. Applicants submit their details and links, complete a short technical assessment, and join the pool if they pass. The opportunity is open to experienced professionals and people just starting their careers, including fresh graduates. Joining the pool does not guarantee immediate work, and eligibility may vary by location based on client-supported regions.",[33],"2026-10-26T23:31:01.961+00:00","2026-10-27T00:04:16.516931+00:00","G2i Inc.","g2i-inc","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/81325e3e-8aa3-4072-81af-51b01692d506.png","RANGE_201_500",[53],[56],[226],{"_17":53,"_61":62,"_63":64,"_65":-5,"_66":67,"_68":-5},[228,229,230],"Applicants may come from software, data, AI/ML, infrastructure, security, design, QA, or product backgrounds.","Experienced professionals and candidates just starting out, including fresh graduates, are welcome.","Eligibility may vary depending on location and client-supported regions.",[232,233,234,235],"Submit accurate application details and relevant links.","Complete a short technical assessment after profile review.","Contribute to client projects when matched based on skills and profile.","Potentially work on evaluations, reinforcement-learning environments, training data, and other AI-related projects.",[237,238,239],"Access to potential projects with top AI labs and fast-growing companies.","Talent-pool matching based on candidate skills and client needs; joining does not guarantee immediate work.","Location eligibility may vary because some client regions are not supported.","https://g2i.co",{"_17":242,"_19":243,"_21":244,"_23":213,"_25":245,"_27":246,"_29":-5,"_30":-5,"_31":247,"_34":250,"_36":251,"_38":251,"_39":-5,"_40":219,"_42":220,"_44":221,"_46":47,"_48":7,"_49":222,"_50":-5,"_51":252,"_54":253,"_57":-5,"_58":254,"_69":256,"_71":260,"_74":264,"_76":-5,"_77":-5,"_78":-5,"_79":-5,"_80":81,"_82":-5,"_83":7,"_84":240},"de2d278a-8bcc-4a95-bc8c-dfd4438e08bc","Tech Talent Pool: Engineers, Data and AI/ML","https://jobs.ashbyhq.com/g2i/fa0008d2-f809-41fa-8f5f-ecad3d624147","Join G2i’s talent pool to be considered for engineering, data, and AI/ML projects with leading AI labs and fast-growing companies. Work may include model evaluations, reinforcement-learning environments, and training data for frontier models.","G2i is building a talent pool of software, data, AI/ML, infrastructure, security, design, QA, and product professionals. Community members may work on projects such as evaluations, reinforcement-learning environments, and training data for frontier models. Applicants complete a profile review and short technical assessment before joining the pool. Project matching depends on client needs, candidate skills, and location eligibility. Fresh graduates and experienced professionals are welcome, but joining the pool does not guarantee immediate work.",[33,248,249],"mid level","senior","2026-10-26T23:27:37.096+00:00","2026-10-27T00:04:15.145113+00:00",[53],[56],[255],{"_17":53,"_61":62,"_63":64,"_65":-5,"_66":67,"_68":-5},[257,258,259],"Background or career interest in software, data, AI/ML, infrastructure, security, design, QA, or product.","Experienced professionals and fresh graduates are welcome.","Eligibility may vary by location because some client regions are not supported.",[261,262,263],"Join a talent pool for potential technology projects matched to your skills and profile.","Contribute to projects such as evaluations, reinforcement-learning environments, and training data for frontier models when matched.","Complete an application with accurate details and links, followed by a short technical assessment.",[265,266,267],"Potential access to projects with top AI labs and fast-growing companies.","Flexible project matching based on client needs and candidate skills.","Joining the pool does not guarantee immediate work.",{"_17":269,"_19":270,"_21":271,"_23":272,"_25":273,"_27":274,"_29":-5,"_30":-5,"_31":275,"_34":276,"_36":277,"_38":277,"_39":-5,"_40":278,"_42":279,"_44":280,"_46":47,"_48":7,"_49":222,"_50":116,"_51":281,"_54":283,"_57":286,"_58":301,"_69":307,"_71":315,"_74":322,"_76":-5,"_77":-5,"_78":-5,"_79":-5,"_80":158,"_82":-5,"_83":7,"_84":327},"453d78ba-ea07-4ba9-803a-62514867f098","2027 US AI Engineering – New College Graduate","https://bitdeer.breezy.hr/p/826249d5dbdc-2027-us-ai-engineering-new-college-graduate","About Bitdeer AI:\nBitdeer AI, a full-stack AI cloud provider (AI Data Center, IaaS, PaaS, MaaS) under Bitdeer Technologies Group and a preferred NVIDIA Cloud Partner, is engineered to power the AI of tomorrow.\nWith the group’s 3 Gigawatts of power capacity deployed and under development globally, Bitdeer holds a decisive advantage in the AI era: the massive energy, physical infrastructure, and compute foundation required to run intelligence at global scale. Operating across strategic international hubs, including the United States, Singapore, and Europe, we build on one core promise: One Cloud, Infinite Possibilities.\nOur Two Core Missions\n:\nTransforming Hyperscale Power into Useful AI: We take the extreme complexity of gigawatt-scale energy grids, liquid-cooled data center topologies, and low-latency networking fabrics, and turn that raw physical power into accessible, high-performance AI Cloud that directly drives real-world intelligence.\nBuilding an Integrated Full-Stack Cloud Platform: We engineer the complete software layer, spanning bare-metal provisioning, managed Kubernetes, distributed training pipelines, high-throughput AI Inference engines, and Model-as-a-Service (MaaS) with serverless APIs, empowering enterprises to seamlessly train, fine-tune, deploy, and serve next-generation AI intelligence.\nWe are seeking\n2027 New College Graduates:\nWhy Start Your Career at Bitdeer AI? We don’t just look at the infrastructure layer, we build across the entire value chain for our full-stack cloud. At Bitdeer AI, you will architect the actual backbone of global artificial intelligence. From foundation-level hardware orchestration and low-latency Inference systems to upper-layer MaaS platforms and AI Agents environments, you will solve high-scale systems challenges that few companies on Earth have the power capacity to attempt.\nYour work will directly power the global AI ecosystem, from ambitious startups and elite research institutions to global enterprises.\nArtificial intelligence is reshaping human potential, but the future of AI relies on real-world compute, reliable infrastructure and engineering, and massive power.\nDon’t just witness the AI revolution. Power it. Join Bitdeer AI, and build the intelligence for infinite possibilities.\nWhat you will be responsible for\nWe are looking for key talents to develop in the following areas:\nCloud Service Platform: Development of large-scale, highly available AI cloud services, including GPU virtual machines, bare-metal services, container services, cloud networking, storage, billing, monitoring, security, and multi-region resource management.\nKubernetes Service Platform: Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads.\nAI Model Training and Inference Platform: Development of distributed training, model fine-tuning, model deployment, inference acceleration, serverless inference, model APIs, model evaluation, and production-grade LLM and multimodal model-serving capabilities.\nAI Agent Platform: Development of enterprise AI Agent platforms, including Agent building, workflow orchestration, tool integration, retrieval-augmented generation, memory systems, sandbox execution, multi-Agent collaboration, evaluation, observability, security, and large-scale Agent runtime infrastructure.\nAdvanced AI Systems: Development of GPU resource scheduling, distributed systems, high-performance networking, cloud-native infrastructure, MLOps and LLMOps platforms, AI application marketplaces, and automated operation systems for large-scale AI infrastructure.\nCareer Opportunities within the Program:\nCloud Platform Engineering\nAI Operations, MLOps & Site Reliability Engineering\nMaaS, Model Serving & AI Training Infrastructure\nAI Agent & Application Engineering\nAI & Cloud Security Engineering\nAI Research\nSuccessful candidates will start in one of the above areas based on the interview assessment and business needs. Opportunities to rotate across different roles will also be provided as part of career development.\nHow you will stand out\nFresh graduates (Bachelors, Masters, PhD) from all disciplines and/or candidates with up to 2 years of related work experience.\nStrong programming ability in one or more languages, including Go, Python, C++, Java, Rust, or related technologies.\nExperience with Kubernetes, Docker, Helm, Terraform, OpenStack, Prometheus, Grafana, Argo, Istio, PostgreSQL, Redis, message queues, distributed storage, or other cloud-native technologies is highly preferred.\nExperience in developing or operating large-scale cloud platforms, Kubernetes platforms, AI training platforms, inference platforms, or Agent platforms is highly preferred.\nDeep enthusiasm for cutting-edge AI infrastructure, cloud-native technologies, and building large-scale, globally distributed systems.\nProven achievements in academics, engineering projects, top-tier publications, open-source contributions, or programming/algorithm competitions.\nA strong ownership mentality, engineering discipline, and a commitment to creating a meaningful impact early in your career as we build the foundation for next-generation AI.\nWhat you will experience working with us\nA culture that values authenticity and diverse perspectives.\nAn inclusive, respectful environment with open workspaces and an energetic, start-up spirit.\nA fast-growing company with opportunities to network with industry pioneers and enthusiasts.\nThe ability to contribute directly and make an impact on the future of the digital asset and AI computing industry.\nInvolvement in new projects and in developing processes/systems.\nPersonal accountability, autonomy, rapid growth, and learning opportunities.\nAttractive benefits and development such as training and mentoring.\nBitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, color, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.","Launch your AI engineering career by building large-scale cloud, Kubernetes, model-serving, and AI agent platforms at Bitdeer AI. New graduates can join areas ranging from cloud infrastructure and MLOps to AI applications, security, and research, with opportunities to rotate across roles.","Bitdeer AI is hiring 2027 new college graduates to develop full-stack AI cloud infrastructure across cloud services, managed Kubernetes, distributed training, inference, MaaS, and AI agent platforms. Responsibilities may include GPU resource scheduling, bare-metal and container services, distributed workload management, model deployment, serverless inference, RAG, agent orchestration, observability, and large-scale AI runtime infrastructure. Candidates should be fresh graduates with a bachelor's, master's, or PhD, or have up to two years of related experience, along with strong programming skills and preferably experience with cloud-native and AI platforms. The program offers placements across cloud platform engineering, MLOps and SRE, model serving and training infrastructure, AI agent engineering, AI and cloud security, and AI research. Career development includes potential rotations, training, mentoring, autonomy, and exposure to globally distributed AI infrastructure.",[33],"2026-10-16T06:05:48.24+00:00","2026-10-16T06:18:15.982525+00:00","BitDeer Technologies Group","bitdeer-technologies-group","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/516b9278-a231-474f-8352-2f65fcf0cd03.png",[118,282],1840021570,[284,285,56],"AI Applications","DevOps",[287,288,289,182,290,291,292,293,294,295,296,297,122,298,299,300],"Argo CD","C++","Docker","Grafana","Helm","Istio","Java","Kubernetes","OpenStack","PostgreSQL","Prometheus","Redis","Rust","Terraform",[302,303],{"_17":118,"_61":62,"_63":125,"_65":-5,"_66":126,"_68":127},{"_17":282,"_61":304,"_63":305,"_65":306,"_66":126,"_68":127},"San Jose","san-jose-california","California",[308,309,310,311,312,313,314],"Fresh graduates with a bachelor's, master's, or PhD in any discipline, or candidates with up to two years of related work experience.","Strong programming ability in one or more of Go, Python, C++, Java, Rust, or related technologies.","Experience with Kubernetes, Docker, Helm, Terraform, OpenStack, Prometheus, Grafana, Argo, Istio, PostgreSQL, Redis, message queues, distributed storage, or other cloud-native technologies is highly preferred.","Experience developing or operating large-scale cloud, Kubernetes, AI training, inference, or AI agent platforms is highly preferred.","Enthusiasm for AI infrastructure, cloud-native technologies, and globally distributed systems.","Demonstrated achievement through academics, engineering projects, publications, open-source contributions, or programming and algorithm competitions.","Strong ownership, engineering discipline, and commitment to creating impact early in a career.",[316,317,318,319,320,321],"Develop large-scale, highly available AI cloud services including GPU virtual machines, bare-metal services, containers, networking, storage, billing, monitoring, security, and multi-region resource management.","Build managed Kubernetes services with GPU orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, and resource isolation.","Develop distributed training, fine-tuning, model deployment, inference acceleration, serverless inference, model APIs, evaluation, and production model-serving systems.","Build enterprise AI agent platforms involving agent construction, workflow orchestration, tool integration, retrieval-augmented generation, memory, sandbox execution, multi-agent collaboration, evaluation, observability, security, and runtime infrastructure.","Work on GPU scheduling, distributed systems, high-performance networking, cloud-native infrastructure, MLOps and LLMOps platforms, AI marketplaces, and automated operations systems.","Join an assigned engineering area based on interview assessment and business needs, with opportunities to rotate across roles.",[323,324,325,326],"Inclusive and respectful workplace with diverse perspectives, open workspaces, and a startup-oriented environment.","Opportunities to network with industry pioneers and contribute directly to new projects and systems.","Personal accountability, autonomy, rapid growth, learning opportunities, training, and mentoring.","Opportunities to rotate across roles as part of career development.","https://bitdeer.com",{"_17":329,"_19":330,"_21":331,"_23":332,"_25":333,"_27":334,"_29":-5,"_30":-5,"_31":335,"_34":336,"_36":337,"_38":337,"_39":-5,"_40":338,"_42":339,"_44":340,"_46":47,"_48":114,"_49":174,"_50":175,"_51":341,"_54":343,"_57":344,"_58":347,"_69":353,"_71":361,"_74":369,"_76":377,"_77":378,"_78":156,"_79":157,"_80":158,"_82":-5,"_83":114,"_84":379},"59d9e3be-7418-4f04-be9c-26e30ce5e28a","Machine Learning Engineer, New Grad - Quora (Remote)","https://jobs.ashbyhq.com/quora/40659fe7-545e-4b08-b6d7-2567b18b9ed3","[Quora is a privately held, \"remote-first\" company https://www.quora.com/q/quora/Remote-First-at-Quora. This position can be performed remotely from anywhere in the US or Canada. Please visit careers.quora.com/eligible-countries http://careers.quora.com/eligible-countries for details regarding employment eligibility by country.]\n\n\n\n\nABOUT QUORA:\n\nQuora’s mission is to grow the world's collective intelligence. To do so, we have two platforms:\n\n - Quora http://quora.com: a global knowledge sharing platform with millions of monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others.\n\n - Poe https://poe.com/: a cloud workspace where millions of users run multiple AI agents on shared context and tools. One subscription, every frontier model, and the collaboration layer that makes them work together.\n\nBehind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world.\n\nThis role will be working on our Quora product.\n\n\n\n\nABOUT THE TEAM AND ROLE:\n\nOur ML team is small and highly collaborative, working on challenging problems that impact hundreds of millions of Quora users. We encourage engineers to think big, experiment with new ideas, and continuously learn and improve. With over 100 ML models in production, engineers have opportunities to take ownership of meaningful projects, work closely with experienced teammates, and quickly see the impact of their work.\n\nWe're building the next generation of AI-powered systems to improve content quality and safety across Quora. By leveraging LLMs and agentic workflows, we're transforming how we detect harmful content, automate complex decisions, and respond to evolving challenges at scale. As a Machine Learning Engineer (New Grad), you'll work alongside experienced engineers to design, evaluate, and deploy these systems in production.\n\nNo previous trust and safety experience is required. You'll learn from the engineers who built these systems.\n\nStack: Python, PyTorch, TensorFlow, Spark, Kubernetes\n\n\n\n\nRESPONSIBILITIES:\n\n - Design, build, and deploy LLM-powered agents to detect and address spam, harassment, and other policy-violating content at Quora's scale\n\n - Develop agentic workflows to automate complex tasks, improving the efficiency and effectiveness of our content and user moderation systems\n\n - Design and improve ML systems that adapt to evolving abuse patterns and new challenges\n\n - Evaluate agent performance through offline evaluations, online experiments, and production monitoring, balancing accuracy, reliability, latency, and cost\n\n - Investigate failure cases, experiment with new approaches, and iterate on solutions to improve system performance\n\n - Identify new opportunities to apply ML and LLMs to content quality and safety across Quora\n\n - Collaborate with experienced engineers and take ownership of projects from early development through production\n\n\n\n\nMINIMUM REQUIREMENTS:\n\n - Availability for meetings and impromptu communication during Quora's “coordination hours https://quora.com/coordination_hours\" (Mon-Fri: 9am-3pm Pacific Time)\n\n - B.S., M.S., or Ph.D. in Computer Science, Engineering or a related technical field, completed or in progress\n\n - Strong understanding of mathematical foundations of Machine Learning algorithms\n\n - Coursework, research, or project experience with LLM applications or transformer models\n\n - Strong knowledge of Python\n\n - A passion for learning and always improving yourself and the team around you\n\n - Able to start full-time in early 2027\n\n\n\n\nPREFERRED REQUIREMENTS:\n\n - Previous software engineering experience via an internship, work experience, open-source contribution or coding competition\n\n - Hands-on experience building and evaluating LLM agents, in projects, research, internships, or production\n\n - Regular use of AI coding tools such as Claude Code or Codex\n\n - Coursework or projects in natural language processing (NLP)\n\n - Genuine interest in content safety and quality\n\n - Passion for Quora's mission and goals\n\n\n\nAt Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture.\n\n\n\n\nADDITIONAL INFORMATION:\n\nWe are accepting applications on an ongoing basis. This role is a backfill for an existing vacancy.\n\nQuora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary.\n\nThere are many factors that will determine the starting compensation, including but not limited to experience, location, education, and business needs.\n\n - US candidates only: For US based applicants, the salary range is $107,360 - $152,900 USD + equity + benefits.\n\n - Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $137,852 - $157,061 CAD + equity + benefits. For all other locations in Canada, the salary range is $128,661 - $146,590 CAD + equity + benefits.\n\n - In equity-eligible countries, we currently also offer a flexible equity program where a portion of equity compensation may be taken as cash.\n\nWe are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.\n\nAI technology may assist in sorting applications and recording interview notes, but all decisions are made by a member of our team.\n\nTo ensure a secure hiring process, all final candidates will undergo identity verification and a comprehensive background check prior to onboarding.\n\nJob Applicant Privacy Notice: https://careers.quora.com/quora-global-job-applicant-privacy-notice\n\n\n\n#LI-JC1\n#LI-REMOTE","Join Quora’s machine learning team as a new graduate engineer building and deploying LLM-powered systems that improve content quality and safety for hundreds of millions of users. You’ll work on agentic workflows, ML evaluation, and production systems alongside experienced engineers.","The role focuses on designing, evaluating, and deploying LLM-powered agents and machine learning systems to detect spam, harassment, and other policy-violating content on Quora. Responsibilities include building agentic workflows, adapting systems to evolving abuse patterns, running offline and online evaluations, monitoring production performance, and investigating failures. Candidates should have a completed or in-progress degree in computer science, engineering, or a related technical field, strong mathematical ML foundations, Python knowledge, and coursework or project experience with LLM applications or transformer models. Preferred qualifications include software engineering experience, hands-on LLM agent experience, NLP coursework, and familiarity with AI coding tools. The role is remote within eligible locations in the US or Canada and is expected to start full-time in early 2027.",[33],"2026-10-15T16:18:53.23+00:00","2026-10-15T18:06:58.080947+00:00","Quora","quora","https://wzishhuxscpbsvxosipt.supabase.co/storage/v1/object/public/company_logos/companies/ccf62b0b-89b1-4eb8-990e-f9144e3b143e.jpg",[118,342],47982,[56],[180,294,122,345,346],"PyTorch","TensorFlow",[348,349],{"_17":118,"_61":62,"_63":125,"_65":-5,"_66":126,"_68":127},{"_17":342,"_61":62,"_63":350,"_65":-5,"_66":351,"_68":352},"remote-can","Canada","CAN",[354,355,356,357,358,359,360],"B.S., M.S., or Ph.D. in Computer Science, Engineering, or a related technical field, completed or in progress.","Strong understanding of the mathematical foundations of machine learning algorithms.","Coursework, research, or project experience with LLM applications or transformer models.","Strong knowledge of Python.","Availability for meetings and communication during Quora’s coordination hours, Monday through Friday from 9 a.m. to 3 p.m. Pacific Time.","Ability to start full-time in early 2027.","Preferred qualifications include software engineering experience through an internship, work experience, open-source contribution, or coding competition; hands-on LLM agent experience; regular use of Claude Code or Codex; NLP coursework or projects; and interest in content safety and quality.",[362,363,364,365,366,367,368],"Design, build, and deploy LLM-powered agents to detect and address spam, harassment, and other policy-violating content.","Develop agentic workflows that automate complex content and user moderation tasks.","Design and improve ML systems that adapt to evolving abuse patterns and new challenges.","Evaluate agent performance through offline evaluations, online experiments, and production monitoring while balancing accuracy, reliability, latency, and cost.","Investigate failure cases, experiment with new approaches, and improve system performance.","Identify opportunities to apply ML and LLMs to content quality and safety.","Collaborate with experienced engineers and own projects from early development through production.",[370,371,372,373,374,375,376],"Remote-first work from eligible locations in the US or Canada.","Medical, dental, and vision coverage.","Equity refreshers and a flexible equity program in eligible countries.","Remote work reimbursement.","Paid time off and employee assistance programs.","Benefits are country-specific and may vary.","Final candidates undergo identity verification and a comprehensive background check before onboarding.",107360,152900,"http://quora.com","actionData","errors"]

Software Engineer

Responsibilities

Categories