Lead MLOps Engineer Relevant Experience: 4+ Years Industrial Experience- 7+ Years Key Responsibilities • Build, deploy, and manage end-to-end ML lifecycle pipelines.

• Automate model training, testing, deployment, and monitoring workflows.

• Implement model versioning, experiment tracking, and model registry solutions.

• Monitor model performance, drift, and operational health in production settings.

• Collaborate with Data Engineers, and DevOps teams to operationalize ML solutions.

• Establish governance, security, access control, and auditability processes for ML platforms.

Required Skills • Solid Python programming skills.

• Experience with ML lifecycle management and deployment automation.

• Hands-on expertise with: o MLflow o Kubeflow o Amazon SageMaker o AWS Step functions o ECS (Elastic Container Services) • Knowledge of Docker and Kubernetes.

• Experience with CI/CD tools and DevSecOps practices.

• Familiarity with Terraform, CloudFormation, or similar IaC tools.





• Understanding of model monitoring, observability, and performance optimization.

Preferred Skills • Hands on experience with AWS.

• Knowledge or hands on experience of Agentcore.

• Knowledge of data engineering tools such as Databricks, Spark, Airflow, Kafka, or Snowflake.

• Understanding of Responsible AI, model governance, and compliance requirements.

• Exposure to Generative AI, LLMOps, and RAG-based solutions.

Qualifications • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.

• Experience taking ML/AI solutions from Proof of Concept (PoC) to Production.

• Robust problem-solving and stakeholder management skills.

AWS, Amazon SageMaker, Observability, MLOps, AI Governance, DevSecOps, AWS Step Functions, Amazon ECS, Python

📌 Lead I Ml Engineering Ml Ops , Agentic Ai And Aws Pune
🏢 UST
📍 Pune