MLOps Engineer
Bear Systems · Delhi, OH · Yesterday
Full-time
About the role
Build the infrastructure around ML: experiment tracking, model registries, deployment pipelines, drift monitoring, and cost controls.
Requirements
- Three or more years in MLOps, platform, or ML infrastructure roles
- Experience with containerised model serving and CI/CD for ML
- Comfortable collaborating with research-leaning ML engineers
Nice to have
- Kubeflow, MLflow, Vertex, SageMaker
- GPU cluster operations
Details
Team: AI & Automation. Location: Delhi NCR / Hybrid. Arrangement: Hybrid. Type: Full-time. Level: Mid. Experience: 3+ years. Posted: 2 October 2026. Closes: 17 January 2027.
Hiring process
- We read it — a person reads every application. No keyword filter.
- Reply — within 5 working days if there is a fit.
- Conversation — 90 minutes with the people you would work with.
- Paid trial — a real, scoped problem. Paid at contract rate.
How to apply
Send your resume, a short note, and anything that shows how you think (portfolio, GitHub, etc.) to info@bearsystems.in. Specifics beat adjectives. Show something you built, not something you managed. Scale, constraints, and trade-offs land better than adjectives. A short note reads better than a long one. Applications close 17 January 2027.