Lead MLOps Engineer
InApp (company site, opens in a new tab)6–10 yrsTrivandrumHybridDirect career pageEst. 18–35 LPA
Posted on 25 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design and manage end-to-end machine learning lifecycle pipelines including training, deployment, and monitoring.
- Implement and maintain scalable, secure, and compliant MLOps platforms with CI/CD, DevSecOps, and Infrastructure as Code practices.
- Monitor and optimize ML infrastructure for performance, scalability, reliability, and cost efficiency in production environments.
Minimum Requirements
- 6-10 years of experience with at least 4 years hands-on in MLOps or ML lifecycle management.
- Strong proficiency in Python and experience with MLflow or Kubeflow, AWS SageMaker, AWS Bedrock, ECS, Docker, CI/CD, and Infrastructure as Code (Terraform or CloudFormation).
- Experience in operationalizing ML solutions from Proof of Concept to Production including model versioning, registry, monitoring, and lifecycle management.
- Work mode: Hybrid/Remote with quarterly 5 days in office for remote employees; Location: Trivandrum/Kochi/Remote.
Ideal Candidate Profile
- Deep experience in building production-grade ML/AI platforms and managing ML workflows in cloud environments, especially AWS.
- Familiarity with DevSecOps, security governance, model monitoring, observability, and automation in ML production systems.
- Experience working collaboratively with Data Engineering, Data Science, DevOps, and application teams to deliver scalable and compliant ML solutions.