Senior / Lead ML Engineer (Databricks MLOps) (India)

Job Role: Senior Or Lead MLOps Engineer (Databricks) Location: Hyderabad (Hybrid) Experience: 8 Years+ Company: Anblicks Role Overview Anblicks is hiring a Senior Level MLOps Engineer with Expertise in Databricks to drive the design, implementation, and scaling of enterprise-grade ML platforms. This role is ideal for a hands-on leader who can own end-to-end MLOps strategy and execution, while mentoring teams and delivering production-ready ML systems on Databricks. You will play a key role in building scalable, reliable, and automated ML pipelines, enabling faster experimentation, deployment, and monitoring of models across business use cases. Key Responsibilities MLOps Leadership & Architecture - - Lead the design and implementation of scalable MLOps frameworks on Databricks - Define and enforce best practices, standards, and governance for ML lifecycle management - Architect end-to-end ML pipelines covering data ingestion, feature engineering, training, deployment, and monitoring - Drive platform standardization for model development and operationalization Databricks & Platform Engineering - - Build and optimize solutions using Databricks ecosystem: MLflow, Unity Catalog, Workflows, Delta Lake, Mosaic AI - Develop high-performance Spark-based pipelines for large-scale data processing - Enable model versioning, experiment tracking, and reproducibility - Ensure scalability, security, and performance of ML platforms MLOps & DevOps Integration - - Implement CI/CD pipelines for ML workflows using GitHub Actions, Jenkins, Terraform, or similar tools - Automate model deployment, monitoring, and retraining pipelines - Work with containerization and orchestration tools like Docker and Kubernetes - Establish observability and monitoring frameworks for ML systems Advanced AI / GenAI Enablement (Valuable to Have) - - Support development of LLM-based and GenAI solutions - Build RAG pipelines and integrate LLMs into enterprise workflows - Evaluate and onboard tools like OpenAI, Bedrock, Vertex AI, LangGraph Stakeholder Collaboration - - Collaborate with Data Scientists, Data Engineers, and Product Teams to productionize ML use cases - Translate business requirements into scalable ML solutions - Provide technical leadership, mentorship, and code reviews Drive continuous improvement and innovation in ML practices Required Skills & Experience - - 712 years of experience in ML Engineering / MLOps / Data Engineering - Strong hands-on experience with Databricks (must-have) - Expertise in MLflow, Unity Catalog, Workflows, Delta Lake - Strong programming skills in Python (mandatory) - Experience with Apache Spark and distributed data processing - Solid understanding of ML lifecycle and model deployment strategies - Experience with CI/CD and DevOps practices - Hands-on experience with Airflow, Kubeflow, or similar orchestration tools - Experience working with AWS / Azure / GCP cloud platforms Preferred Qualifications - - Databricks Certification (Associate / Professional / Architect) - Experience with GenAI / LLM ecosystems - Familiarity with vector databases (Pinecone, ChromaDB, etc.) - Experience with Docker, Kubernetes, and infrastructure as code (Terraform) - Exposure to model monitoring and observability tools Leadership & Behavioral Competencies - - Strong ownership mindset with the ability to lead from the front - Excellent problem-solving and analytical thinking - Ability to manage multiple priorities in a fast-paced environment - Strong communication skills with both technical and business stakeholders Mentorship experience and team collaboration skills Why Join Anblicks - - Work on cutting-edge Databricks and AI/ML platforms - Opportunity to lead enterprise-scale ML transformations - Collaborative and innovation-driven engineering culture - Exposure to modern data + AI ecosystem (Snowflake, Databricks, GenAI) .