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Research Engineer, Model Inference & Serving - Paris

H Company -
Paris (75)

Soumettre votre candidature

Détails de l'emploi

Temps plein

Qualifications

Rust
Go
Kubernetes
C++
Systèmes distribués
Deep learning
Intelligence artificielle
Python

Description complète du poste

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

If you want to change the status quo in AI, join us.

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