MLOps Engineer (AI Infrastructure)
- Source: LinkedIn
- Stackbinary
- On-site
- Mumbai
- Full-Time
- Mid level
Job Description
About The Role Own the platform our AI runs on. You will make deployment boring, cost visible, and model updates something we test rather than discover.
What You’ll Do
Build and operate model serving infrastructure
Implement monitoring for quality drift, latency and spend
Build CI pipelines that run evaluations before a model change ships
Manage model registries and rollback paths
Optimise inference cost through routing, caching and batching
Support private and self-hosted deployments for regulated clients
What You’ll Bring
2+ years in DevOps, platform or ML infrastructure
Strong Docker and cloud experience on AWS or GCP
Python and comfort with CI/CD tooling
Understanding of GPU cost and capacity planning
Monitoring and alerting instincts
Nice to Have
vLLM, Ray or similar serving stacks
Kubernetes in production
Experience self-hosting open-weight models
What You’d Build
These aren’t hypothetical projects, they’re live products you can try before your first interview.
The StackBinary MarTech Suite, The full product line, every system we ship, most with live demos.
Why Join StackBinary™?
Flexible working hours
Remote-friendly culture
Learning & development budget
High-ownership projects
Pragmatic engineering culture
Work with cutting-edge tech
Ready to Apply?
Join our team of builders who love shipping quality software.
We connect with shortlisted candidates through LinkedIn or our official email IDs.
Follow StackBinary on LinkedIn →
Questions about this role?
Skills
- drift
- Docker
- amazon-web-services
- google-cloud-platform
- Python
- vllm1
- Kubernetes
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