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
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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
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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
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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)
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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
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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
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Required Skills & Experience
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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
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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
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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
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Why Join Anblicks
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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)
