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

Role

Research Engineer, Model Inference & Serving - London

Locations

Hybrid London

Published

April 10

Deadline

August 16

Tags for this job

Python Kubernetes AI Go Rust

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