Job Role: Senior Or Lead –MLOps Engineer (Databricks)

Location: Hyderabad (Hybrid)

Experience: 8 Years+

Company: Anblicks

Role Overview

Anblicks is hiring a Senior Level MLOpsEngineer 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)

Senior / Lead ML Engineer (Databricks MLOps)