Senior / Lead ML Engineer (Databricks MLOps)

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 (Good 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 7–12 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)