Senior ML OPs Engineer - Machine Learning Platform

Checking deployment pipelines for ML models.

Review Code changes and pull requests from the data science team.

Triggers CI/CD pipelines after code approvals.

Monitors pipelines and ensures all tests pass and model artifacts are generated/stored correctly.

Deploys updated models to prod after pipeline completion.

Works closely with the software engineering and DevOps team to ensure smooth integration.

Containerize models using Docker and deploy on cloud platforms (like AWS/GCP/Azure).

Set up monitoring tools to track various metrics like response time, error rates, and resource utilization.

Establish alerts and notifications to quickly detect anomalies or deviations from expected behavior.

Collaborate with the data science team to develop updated pipelines to cover any faults and Analyze monitoring data, logs, files, and system metrics.

Documenting and troubleshoots, changes, and optimization.

Work alongside our Product, UX, and Prototype Engineering teams, you’ll leverage your experience and expertise in the AI space to influence our product roadmap, developing innovative solutions that add additional capabilities to our product suite