Machine Learning Engineer - Python
Summary
CGI in Chennai (5–7 yrs) is hiring a Machine Learning Engineer to build and maintain data sourcing pipelines (ETL, Denodo, Airflow), manage Python environments, enforce security/vulnerability practices, and support CI/CD deployment of containerized ML models (Docker/Kubernetes), collaborating with Brussels-based teams.
Role & responsibilities
Please Read JD carefully and apply
As a ML Engineer you will be part of a team that is responsible of the following operational activities:
- Design, Maintain and optimize data sourcing pipelines using ETL, CFT, Denodo (data virtualization), and Airflow to ingest, transform, and expose data for AI/ML use cases. Ensure seamless integration of new data sources (internal/external APIs, databases, or streaming platforms) while adhering to data governance and latency requirements.
- Maintain Python environments by proactively auditing dependencies, upgrading obsolete libraries, and enforcing version compatibility across development, testing, and production. Document and communicate changes to minimize disruption.
- Enforce Vulnerability management in production code by:
- Conducting regular security scans and patching critical vulnerabilities in pipelines, APIs, and dependencies.
- Implementing secure coding practices and collaborating with cybersecurity teams to mitigate risks.
- Automating compliance checks in CI/CD pipelines to block vulnerable code from deployment.
- Understand & support CI/CD workflows (Jenkins, GitLab CI/CD) for containerized ML models (Docker/Kubernetes), ensuring seamless deployment, versioning, and rollback capabilities.
- Troubleshoot and resolve complex incidents in QA/Production, ensuring minimal downtime and continuous improvement of AI services.
- Collaborate with Data Scientists and PROD IT teams to define production-ready architectures, balancing technical feasibility with business requirements (real-time responses, high-volume processing).
- Promote Software Engineering best practices code quality, security, logging, —within your squad.
- Stay ahead of AI/ML advancements (LLMs, Agentic AI) and propose innovative solutions to optimize workflows and reduce time-to-market.
Preferred candidate profile
You will drive the industrialization of AI solutions, ensuring they are reliable, scalable, and aligned with technical best practices. You will act as the key bridge between Data Scientists and IT Production team, translating business needs into production-ready ML pipelines while anticipating technological advancements.
As part of the Machine Learning Engineers Chapter, you will collaborate closely with Brussels-based teams, maintaining seamless Data sourcing for the Tribes AI use cases, and help the teams maintain a high level of obsolescence management and security in the python environments. Your role is both strategic and operational, transforming prototypes into high-performance AI services while fostering excellence in MLOps, code quality, and cross-team collaboration.