Level

H Company

Research Engineer, Model Inference & Serving - London

H Company is hiring a Research Engineer, Model Inference & Serving - London (United Kingdom). Level rates it ; you can apply on H Company.

Level's read on this job

  • On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
  • The posting allows some remote work.
  • Tools and skills the posting cites include Llama, vLLM and PyTorch.
  • Level lists 34 other open roles at H Company.

AI in this role

llamavllmpytorchjax
ai-agents
Research Engineer, Model Inference & Serving

About H: H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step tasks typically performed by humans, AI agents will help unlock full human potential. H is hiring the world's best AI talent, seeking those who are dedicated as much to building safely and responsibly as to advancing disruptive agentic capabilities. We promote a mindset of openness, learning, and collaboration, where everyone has something to contribute.

About the Team: The Inference team builds and operates the systems that serve H's foundational models in production. We focus on multimodal inference and serving for Computer Use Agents, optimizing across both the inference engine layer (e.g., vLLM, SGLang) and the model serving layer (e.g., disaggregated inference, intelligent routing). Agentic inference brings constraints around context length, multimodality, and tool calls, which we address by co-designing with the Models team on training-time choices and with the agent teams on how models are deployed. We operate at the intersection of research and production, translating cutting-edge inference techniques into the systems that power H's next generation of agents. We are looking for strong engineers excited about inference to join the team and help shape the systems behind superintelligent AI.

Key Responsibilities:

  • Build and operate the inference stack that serves H's multimodal agentic models

  • Improve latency, throughput, and cost of model serving across the stack

  • Research and implement inference techniques tailored to agent workloads

  • Co-design with the Models team on training-time decisions that affect inference

  • Collaborate with cross-functional teams to integrate inference into agentic AI products

  • Evaluate inference, serving, and hardware platforms, and communicate findings to stakeholders

  • Stay current with advancements in inference, model serving, and accelerator technology

Requirements:

  • Technical skills:

    • Strong software engineering track record

    • Proficient in Python and at least one systems language (Rust, C++, or Go)

    • Hands-on experience with deep learning frameworks (PyTorch, JAX), preferably in an industry setting

    • Solid distributed systems fundamentals

    • Experience working in a modern cloud environment and with production ML infrastructure (Kubernetes, etc.)

    • Working knowledge of modern ML, including transformers and multimodal architectures

  • Research skills:

    • Research engagement: an advanced degree with research output, or publications at top-tier AI or systems venues (e.g., NeurIPS, ICML, MLSys, OSDI), research internships, or substantive open-source contributions

  • Soft skills:

    • Excellent communication and presentation skills

    • Strong collaboration and teamwork skills

    • Passion for inference and AI

  • Preferred qualifications:

    • Startup experience

    • Hands-on experience with inference frameworks (vLLM, SGLang, TensorRT-LLM)

    • Writing or modifying GPU kernels (CUDA, Triton, etc.)

    • Edge or on-device inference experience (llama.cpp, MLX, ONNX Runtime, etc.)

    • Experience with quantization, speculative decoding, disaggregated inference or KV-cache compression

    • Experience with multimodal models and/or agentic systems

Location:

  • Paris or London.

  • This role is hybrid, and you are expected to be in the office 3 days a week on average.

  • Please expect some travel between offices on a reasonable cadence (e.g., every 4-6 weeks).

What We Offer:

  • Join the exciting journey of shaping the future of AI

  • Collaborate with a fun, dynamic and multicultural team, working alongside world-class AI talent in a highly collaborative environment

  • Enjoy a competitive salary

  • Unlock opportunities for professional growth, continuous learning, and career development

How we rate this

Research Engineer, Model Inference & Serving - London at H Company rates 100 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsLlamavLLMPyTorchJAX

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Walk me through how you've used Llama in your day-to-day work.
  3. What are the limits of vLLM that you've run into, and how did you work around them?
  4. What's a project where you used PyTorch hands-on?
  5. Walk me through how you've used JAX in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: AI agents, Llama, vLLM, PyTorch, and JAX. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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