ML Platform Engineer, Distributed Training
Egen
- Pay
- $159.3K to $219.2K
- a year
- Location
- United States
- Work style
- Remote only
- Job type
- Full time
- Posted
- Oct 19
- 3 days ago
Career path
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About the company
Egen
Information technology and services · 501 to 1,000 employees
Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results. If this describes you, we want you on our team.
What you'll do
- Take AI features from initial prototype to robust, scalable production services
- Work on document intelligence and RAG pipelines
- Solve for latency, error handling, and cost optimization
- Collaborate with clients to translate business needs into high-performance AI architectures
What you need
- 5+ years of engineering experience, with recent hands-on work on GPU training infrastructure and large-scale training.
- Strong Python software engineering: production-quality code, tests and code review. Coding is central to this role, not an afterthought.
- GKE and GPU scheduling: Kubernetes on Google Cloud with GPU node pools, job queueing (Kueue or similar), and capacity and quota management.
- Distributed PyTorch and Ray Train: has personally run and debugged multi-node training jobs.
- RDMA and GPU networking: GPUDirect/RDMA, NCCL tuning, multi-node GB200 (or H200) topology.
- Benchmarking and evals: has designed performance benchmarks and model evaluations, and used them to make decisions.
- Deep enough understanding to explain how and why a system works, without leaning on AI coding tools to carry the reasoning.
- A track record of visible ownership: present, communicative, and accountable on a demanding team.
Key skills
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