About this role
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 develops and enhances the inference stack for serving H-models that power our agent technology. The team focuses on optimizing hardware utilization to reach high throughput, low latency and cost efficiency in order to deliver a seamless user experience.
Key Responsibilities:
Develop scalable, low-latency and cost effective inference pipelines
Optimize model performance: memory usage, throughput, and latency, using advanced techniques like distributed computing, model compression, quantization and caching mechanisms
Develop specialized GPU kernels for performance-critical tasks like attention mechanisms, matrix multiplications, etc.
Collaborate with H research teams on model architectures to enhance efficiency during inference
Review state-of-the-art papers to improve memory usage, throughput and latency (Flash attention, Paged Attention, Continuous batching, etc.)
Prioritize and implement state-of-the-art inference techniques
Requirements:
Technical skills:
MS or PhD in Computer Science, Machine Learning or related fields
Proficient in at least one of the following programming languages: Python, Rust or C/C++
Experience in GPU programming such as CUDA, Open AI Triton, Metal, etc.
Experience in model compression and quantization techniques
Soft skills
Collaborative mindset, thriving in dynamic, multidisciplinary teams
Strong communication and presentation skills
Eager to explore new challenges
Bonuses:
Experience with LLM serving frameworks such as vLLM, TensorRT-LLM, SGLang, llama.cpp, etc.
Experience with CUDA kernel programming and NCCL
Experience in deep learning inference framework (Pytorch/execuTorch, ONNX Runtime, GGML, etc.)
Location:
Paris or London.
This role is hybrid, and you are expected to be in the office 3 days a week on average.
The final decision for this will lie with the hiring manager for each individual role
What We Offer:
Join the exciting journey of shaping the future of AI, and be part of the early days of one of the hottest AI startups
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.