Senior Machine Learning Engineer, LLM Inference Optimization

Role description

Role Overview

Nebius is building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment. The Senior Machine Learning Engineer owns substantial model and endpoint optimization projects end to end, debugging difficult serving problems independently and delivering measurable improvements without needing heavy supervision.

What You Will Do

Own optimization work for specific model families, customer endpoints, or serving backends. Run engine comparisons and recommend practical serving configurations for specific workloads. Deploy, configure, benchmark, and extend inference engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, or similar systems.

Why It Might Be a Fit

The ideal candidate has strong Python and PyTorch engineering skills, hands-on experience deploying or optimizing LLM, VLM, or high-throughput transformer inference systems, and a strong understanding of transformer inference bottlenecks.

Requirements

• 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

Benefits

• 100% company-paid medical, dental, and vision coverage for employees and families
• Up to 4% company match with immediate vesting in 401(k) plan
• 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers in parental leave
• Up to $85/month for mobile and internet in remote work reimbursement
• Company-paid short-term, long-term and life insurance coverage in disability & life insurance