Machine Learning Engineer II
Demandbase3 hours ago
Hyderābād, IndiaMid Level
H1B Sponsor
Responsibilities
- Design, develop, and productionize machine learning and GenAI solutions for Company and Domain intelligence.
- Build data and feature pipelines for structured, semi-structured, and unstructured first-party and third-party data.
- Develop LLM applications using RAG, semantic retrieval, tool and function calling, agentic workflows, enterprise APIs, and internal data sources.
- Create reusable AI services, APIs, orchestration components, evaluation datasets, automated evaluation frameworks, and feedback loops.
- Define quality metrics and acceptance criteria covering accuracy, relevance, grounding, latency, reliability, and cost.
- Analyze production failures and improve data, models, prompts, retrieval strategies, and agent behavior.
- Apply guardrails, grounding, monitoring, and data-quality controls to improve system reliability.
- Own features end to end from design and evaluation through deployment, monitoring, and support.
- Operate cloud-native AI services and improve quality, reliability, latency, scalability, and cost.
- Apply engineering practices involving distributed systems, concurrency, performance, testing, debugging, and code reviews.
Requirements
- 5–7 years of experience in Machine Learning Engineering, Applied ML, Data Science Engineering, or related areas.
- Strong Python programming and software engineering fundamentals; Scala experience is a plus.
- Hands-on experience building and productionizing machine learning models or ML-driven applications.
- Experience with Generative AI and LLM technologies, including LLM APIs or open-source models, embeddings, prompt engineering, and RAG.
- Strong understanding of model training, feature engineering, model evaluation, experimentation, and inference.
- Experience with NLP, transformers, embeddings, or other techniques for unstructured data.
- Strong SQL knowledge and experience working with large datasets.
- Working knowledge of at least one cloud platform: AWS, GCP, or Azure.
- Experience with Spark, Kafka, Airflow, or similar large-scale data-processing technologies is preferred.
- Experience with entity resolution, record linkage, classification, data mining, data enrichment, large-scale first-party or third-party datasets, or heterogeneous enterprise data is preferred.
- Experience with Kubernetes, Docker, CI/CD, ML deployment workflows, MLOps/LLMOps, experiment tracking, model and prompt versioning, and production ML monitoring is preferred.
Benefits
- Group medical, personal accident, and term life insurance.
- Preventive dental, vision, and OPD healthcare coverage.
- Mental health support and a fitness benefit.
- Car lease policy and gratuity for long-term financial well-being.
- The company promotes diversity, equity, inclusion, and equal opportunity.
Tech Stack
Apache AirflowApache KafkaApache SparkAWSAzureDockerGoogle Cloud PlatformKubernetesPandasPythonScalaSQL
Categories
About Demandbase
Demandbase is the only pipeline AI platform that empowers GTM teams to automate growth at scale. With a unified view of data, insights, actions, and outcomes, B2B enterprises can seamlessly align and execute their account-based GTM strategies with confidence. Thousands of businesses trust Demandbase to maximize revenue, minimize waste, and consolidate their data and tech stacks – all in one platform. For more information about how Demandbase can help you accelerate your pipeline at scale, visit www.demandbase.com