MLOps Senior / Lead

Role: Senior / Lead – MLOps Engineer

Location: Hyderabad

Experience: 8+ Years

Early Joiners Preferred Role Overview We are looking for a highly skilled

Senior / Lead – MLOps Engineer (Databricks) to design, build, and operationalize enterprise-scale AI/ML platforms and MLOps solutions. The ideal candidate will have strong expertise in

Databricks, MLOps, GenAI, Cloud Engineering, and ML Platform Architecture with hands-on experience deploying large-scale machine learning and GenAI solutions in production environments. This role requires deep technical expertise in ML lifecycle management, Databricks-native MLOps capabilities, CI/CD automation, distributed data processing, and cloud-native AI platforms.

What You Will Do

• Design, develop, and operationalize enterprise-scale MLOps platforms and ML deployment pipelines using Databricks.
• Build scalable ML workflows for data preparation, model training, deployment, monitoring, and inference.
• Architect and implement hyperscale MLOps and orchestration pipelines for production ML workloads.
• Collaborate with Data Scientists, ML Engineers, Product Teams, and Software Engineers to deliver AI/ML solutions at scale.
• Develop and optimize GenAI and LLM-powered applications, RAG pipelines, and AI automation frameworks.
• Implement CI/CD automation and Infrastructure-as-Code (IaC) using Terraform, GitHub Actions, Jenkins, and Databricks Asset Bundles.
• Drive standardization of ML platform architecture, governance, deployment practices, and observability frameworks.
• Build scalable model inference solutions using Spark, Databricks, EMR/DataProc, and distributed computing frameworks.
• Evaluate and improve platform scalability, reliability, monitoring, security, and operational efficiency.
• Conduct architecture reviews and ensure AI/ML platforms comply with enterprise governance and security standards.
• Lead technology evaluations and drive innovation across AI/ML, MLOps, and GenAI ecosystems.
• Mentor engineering teams and promote best practices in ML engineering, automation, and platform modernization.

Required Skills & Experience MLOps & Databricks

• Strong expertise in MLOps, ML lifecycle management, and enterprise-scale ML platform engineering.
• Hands-on experience architecting and deploying ML solutions using Databricks.
• Strong experience with:
• Databricks MLflow
• Unity Catalog
• Mosaic AI
• Databricks Workflows
• Databricks Asset Bundles

GenAI & LLM Engineering

• Experience building GenAI and LLM-based applications using:
• OpenAI APIs
• Amazon Bedrock
• Vertex AI
• LangGraph or similar agentic frameworks
• Experience with RAG pipelines, vector databases, and LLM orchestration frameworks.
• Familiarity with Pinecone, ChromaDB, or similar vector databases.

ML & Data Engineering Experience with:

• Apache Spark
• Databricks
• EMR / DataProc
• Airflow / Kubeflow / DAGster / MLflow
• Snowflake / Redshift
• AWS Glue, Lambda, Step Functions, AWS Batch

Cloud & DevOps

• Strong experience with AWS, Azure, or GCP cloud platforms.
• Expertise in Terraform, CI/CD, GitHub Actions, Jenkins, and deployment automation.
• Hands-on experience with Docker and Kubernetes.
• Strong understanding of distributed systems, observability, scalability, and fault tolerance.

Programming & AI Frameworks

• Strong programming skills in Python.
• Experience with ML/AI frameworks such as:
• TensorFlow
• PyTorch
• Scikit-learn
• H2O.ai
• Hugging Face

Leadership & Architecture

• Experience leading enterprise AI/ML architecture and platform modernization initiatives.
• Strong problem-solving, stakeholder management, and technical communication skills.
• Ability to collaborate effectively with both technical and business teams.

Preferred Qualifications

• Databricks Certification (Preferred/Required).
• Experience with LLM observability and AI governance platforms.
• Strong understanding of ML platform security, governance, and compliance best practices.
• Exposure to scalable AI platform architecture and distributed ML systems.
• Passion for innovation, automation, and AI/ML platform engineering.