Role overview

Senior ML Engineer (Token Factory)

Requirements and responsibilities

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The role

  • Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
  • Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
  • Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We expect you to have:

  • A profound understanding of theoretical foundations of machine learning and transformer architecture.
  • Experience profiling GPU workloads using Nsight, PyTorch profiler, or similar tools
  • Understanding of GPU memory hierarchy and compute/memory tradeoffs
  • Familiarity with important ideas in LLM space, such as MHA, RoPE, KV-cache, Flash Attention, and quantisation
  • Understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)
  • Strong software engineering skills (we mostly use Python)
  • Deep experience with modern deep learning frameworks
  • Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing
  • Strong communication and leadership abilities

Nice to have:

  • Experience working with open-source inference engines (vLLM, SGLang, TensorRT-LLM), including contributions
  • Experience with kernel languages or DSLs such as Triton, Cute, CUTLASS, CUDA
  • A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
  • Strong engineering skills, including experience in developing large distributed systems or high-load web services.
  • Open-source projects that showcase your engineering prowess
  • Excellent command of the English language, alongside superior writing, articulation, and communication skills.

Benefits & Perks:

  • Competitive compensation
  • Career growth and learning opportunities
  • Flexibility and ownership
  • Collaborative and innovative culture
  • Opportunity to work on impactful AI projects
  • International environment and talented teams
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Browse stack
FocusMachine Learning EngineeringRole area
Seniority signalSeniorCandidate level
StackCI/CD, LLM, PythonPrimary skills
Location42 accepted countriesEligibility

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