Senior Machine Learning Engineer, LLM Inference Optimization

Details

Nebius Token Factory is building AI training and model post-training capabilities for frontier model improvement. This role owns the infrastructure that makes large-scale training and reinforcement learning experiments reliable, reproducible, and efficient. The work sits at the intersection of distributed systems, GPU performance, model training frameworks, reinforcement learning pipelines, and production engineering.

A Senior Machine Learning Engineer owns substantial model and endpoint optimization projects end to end, independently debugs difficult serving problems, and delivers measurable improvements with minimal supervision.

Responsibilities

• Own optimization work for specific model families, customer endpoints, or serving backends.
• Run engine comparisons and recommend practical serving configurations for specific workloads.
• Debug model quality or performance regressions during production rollouts.
• Optimize LLM and VLM endpoints for latency, throughput, memory efficiency, GPU utilization, quality, and cost per token.
• Deploy, configure, benchmark, and extend inference engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, or similar systems.
• Build and productionize model-compression workflows, including quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery.
• Implement or integrate speculative decoding, draft-model approaches, KV-cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving.
• Build reproducible benchmark harnesses for TTFT, TPOT, tokens per second per GPU, p95/p99 latency, GPU memory, reliability, and cost per token.
• Partner with GPU kernel engineers and platform engineers to diagnose bottlenecks across model code, kernels, runtime, scheduler, gateway, and cluster layers.
• Write clear design documents, performance reports, rollout plans, and customer-facing technical explanations.

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.
• Ability to reason quantitatively about latency, throughput, quality, utilization, and cost trade-offs.
• Strong communication skills and the ability to collaborate with research, kernel, infrastructure, product, and customer teams.

Nice-to-Haves

• Experience with quantization-aware training, post-training quantization, FP8, INT8, INT4, NVFP4, MXFP4, AWQ, GPTQ, SmoothQuant, or related techniques.
• Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or other inference acceleration methods.
• Experience with agentic workloads, including tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration.
• CUDA or Triton familiarity, even if the role is not primarily a kernel-engineering role.
• Open-source contributions to vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, KServe, or related projects.

Benefits

• 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) plan with up to a 4% company match and immediate vesting.
• 20 weeks of paid parental leave for primary caregivers and 12 weeks for secondary caregivers.
• Remote work reimbursement of up to $85 per month for mobile and internet.
• Company-paid short-term, long-term, and life insurance coverage.
• Competitive compensation and benefits packages.
• Career growth and learning opportunities.
• Flexibility and ownership.
• Collaborative and innovative culture.
• Opportunity to work on impactful AI projects.
• International environment and talented teams.

Nebius is an equal opportunity employer committed to fostering an inclusive and diverse workplace. Applicants must be authorized to work in the country in which they apply and must provide proof of employment eligibility as a condition of hire.