Machine Learning Engineer

Work Location:

Bangalore
Work Mode:

Hybrid
Experience:

5+ Years

Job Description:
Build, deploy, and scale machine learning platforms and distributed ML workloads.
Ray.io is a key platform, but candidates do not need prior Ray experience if fundamentals are strong.
Core Requirements (Must-Have):
Strong experience as an ML Platform Engineer
Hands-on experience with:
TensorFlow
PyTorch
LLMs / generative AI models
Proven ability to:
Build ML pipelines
Deploy models into production
Run ML workloads at scale
Strong Kubernetes knowledge (mandatory)
Solid understanding of distributed systems and cloud-native architecture
Ray.io Expectations:
Prior Ray experience is a plus, not a blocker
Candidate should be capable of learning Ray quickly (~1 month ramp-up)
Focus is on using Ray for:
Distributed training
Parallel processing
Scalable ML workloads