AI/ML Engineer / Data Scientist - Databricks

Job Title:AI/ML Engineer / Data Scientist - with Databricks focus

Experience: 8+YearsWork type: Remote (India)

Key Responsibilities:• Develop, deploy, and maintain scalable MLOps pipelines for both traditional ML and Generative AI use cases leveraging Databricks (Unity Catalog, Delta Tables, Inference Tables, Mosaic AI).• Operationalize large language models (LLMs) and other GenAI models, ensuring efficient prompt engineering, fine-tuning, and serving.• Implement model tracking, versioning, and experiment management using MLflow.• Build robust CI/CD pipelines for ML and GenAI workloads to automate testing, validation, and deployment to production.• Use Vertex AI to manage training, deployment, and monitoring of ML and GenAI models in the cloud.• Integrate high-quality, governed data pipelines that enable ML and Generative AI solutions with strong lineage and reproducibility.• Design and enforce AI Governance frameworks covering model explainability, bias monitoring, data access, compliance, and audit trails.• Collaborate with data scientists and GenAI teams to productionize prototypes and research into reliable, scalable products.• Monitor model performance, usage, and drift — including specific considerations for GenAI systems such as hallucination checks, prompt/response monitoring, and user feedback loops.• Stay current with best practices and emerging trends in MLOps and Generative AI.

Key Qualifications:

Must Have Skills:

• 3+ years of experience in MLOps, ML Engineering, or related field.• Hands-on experience with operationalizing ML and Generative AI models in production.• Proficiency with Databricks (Unity Catalog, Delta Tables, Mosaic AI, Inference Tables).• Experience with MLflow for model tracking, registry, and reproducibility.• Strong understanding of Vertex AI pipelines and deployment services.• Expertise in CI/CD pipelines for ML and GenAI workloads (e.g., GitHub Actions, Azure DevOps, Jenkins).• Proven experience in integrating and managing data pipelines for AI, ensuring data quality, versioning, and lineage.• Solid understanding of AI Governance, model explainability, and responsible AI practices.• Proficiency in Python, SQL, and distributed computing frameworks.• Excellent communication and collaboration skills.

Nice to Have:

• Experience deploying and monitoring Large Language Models (LLMs) and prompt-driven AI workflows.• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) architectures.• Infrastructure-as-Code experience (Terraform, CloudFormation).• Experience working in regulated industries (e.g., finance, Retail) with compliance-heavy AI use cases.