# Senior Machine Learning Engineer, LLM Inference Optimization at Nebius

- Company: Nebius
- What the company does: Build and scale faster on the purpose-built AI cloud, engineered from silicon to API. Backed by Accel.
- Company website: https://nebius.com/
- Type: Startups (AI role)
- Level: Senior
- Location: Palo Alto, California, United States
- Work setup: On-site
- Posted: 2026-07-22
- Apply by: 2026-10-12
- Apply: https://careers.nebius.com/?gh_jid=4921522101
- Page: https://www.1752.vc/careers/jobs/nebius-senior-machine-learning-engineer-llm-inference-optimization/

## About the role

Nebius Token Factory is building fast, reliable, and cost-efficient inference services for frontier models. As a Senior Machine Learning Engineer on our Applied AI team, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, inference engines, serving architecture, and benchmarking, with a focus on improving latency, throughput, memory efficiency, GPU utilization, and cost per token while maintaining model quality and reliability.

## What they're looking for

- Strong Python and PyTorch engineering skills
- Hands-on experience deploying or optimizing LLM, VLM , or high-throughput transformer inference systems
- Practical knowledge of at least one modern inference stack such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, Ray Serve, KServe, or equivalent internal systems
- Strong understanding of transformer inference bottlenecks, including KV cache, attention, memory bandwidth, batching, parallelism, and long-context serving
- Ability to reason quantitatively about latency, throughput, quality, utilization, and cost tradeoffs
- Strong communication skills and ability to collaborate with research, kernel, infrastructure, product, and customer teams

Tags: ML