
H · Hybrid Paris
RESEARCH ENGINEER, MODEL INFERENCE & SERVING About H: H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step t...
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.
NeurIPS, ICML, MLSys, OSDI), research internships, or substantive open-source contributions
environment
If you want to change the status quo in AI, join us.
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 Models team builds the foundational models that power our cutting-edge agentic technology. We focus on training techniques to optimize model capabilities specifically for agent applications. This allows us to achieve the best performance at a given inference cost. Our work spans the development of Large Language Models (LLMs) and Vision-Language Models (VLMs), enabling agents to perceive, understand, and act within complex environments. We are deeply involved in enhancing these models through training methods with a focus on improved instruction following, tool use, and interaction with dynamic environments via large-scale reinforcement learning and reward modeling. We operate at the intersection of research and product, translating cutting-edge research into practical solutions that drive the next generation of AI. We are looking for bright, motivated individuals to join our ranks and shape the future of superintelligent AI. Key Responsibilities: * Develop and train advanced LLMs and VLMs, including multimodal architectures * Research and implement training methods for enhanced capabilities like instruction following and tool use * Design and optimize data pipelines and training systems for large-scale distributed training * Collaborate with cross-functional teams to integrate models into agentic AI systems * Evaluate model performance and communicate findings to stakeholders * Stay current with advancements in LLMs, VLMs, and related fields Requirements: * Technical skills: * Strong programming skills (Python, Git) * Expertise in deep learning frameworks (PyTorch, JAX, TensorFlow) * Experience with large-scale distributed training of LLMs and VLMs * Hands-on experience with LLM training, alignment, and reinforcement learning * Knowledge of multimodal architectures and applications * Research skills: * Publications in top-tier AI conferences (e.g., NeurIPS, ICML, CVPR, ACL, ICCV) * Advanced degree (PhD or MSc) in a relevant field (e.g., ML, DL, NLP, CV) * Soft skills: * Excellent communication and presentation skills * Strong collaboration and teamwork skills * Passion for AI and problem-solving * Bonuses: * Industry experience * Experience in LLM training with RL * Experience with data processing techniques 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, 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.
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 Infrastructure team aims to make it seamless for our researchers and engineers to access and use the infrastructure they need to do their job. The team also ensures the underlying infrastructure for our public services is robust, reliable and scalable. Members of the Infra team are uniquely positioned to impact all areas of H, from building everything from our foundational models to our agents, all the way to our public services. Key Responsibilities: * Designing and managing the infrastructure to support * Research efforts in Model and Agent development incl. training infrastructure, data pipelines and inference. * Product Engineering efforts on H Company’s agent platform including client-facing APIs and agent runtimes within various deployment scenarios (multi-tenant and on-prem). * Setup and maintain observability and monitoring strategies. Requirements: * MUST HAVE * Observability and monitoring (Datadog, Prometheus, Grafana, …) * Good knowledge of a modern programming language (ideally Python or JS/Typescript) * NICE TO HAVE * ML Ops or Data Engineering * Experience architecting and deploying distributed systems on public cloud (AWS, Azure, GCP) * Containerization and orchestration tools (Docker, Kubernetes, …) * Infrastructure as code (CDK, Terraform, ...) * CICD management experience (Github Actions, Gitlab CI, TeamCity, ...). Location: * Paris or London. * This role is hybrid, and you are expected to be in the office 3 days a week on average. 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.
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 Agent team defines new learning algorithms and agent paradigms to push the frontiers of agentic systems. We build upon foundation models and reinforcement learning to develop new approaches to train artificial general agents and work closely with the LLM/VLM and Safety teams to explore new directions. This is a heavily engineering-focused role embedded within the research team. You will be responsible for defining the architecture and building the robust, scalable systems that underpin our research efforts. Your work will translate cutting-edge research concepts into high-performance, production-quality platforms, enabling the next generation of agentic AI. Key Responsibilities: * Research & Leadership: Design and develop new agents, proposing new research directions, e.g., combining state-of-the-art RL with foundation models (LLMs/VLMs). * Algorithm & Systems Design: Design, implement, and scale complex, high-performance systems for training large-scale agents. This includes both the foundational infrastructure and the novel algorithms, reward models, and sophisticated training environments. * Research-to-Production: Collaborate closely with researchers and engineers to implement, test, and productionize new agent logics, learning algorithms, and system architectures. * Evaluation & Reliability: Create, manage, and scale massive benchmarks and evaluation systems to rigorously track agent capabilities. You will own system reliability, scalability, and observability for our entire research infrastructure. * Mentorship & Standards: Mentor and guide other engineers and researchers on the team, fostering technical excellence. You will establish and enforce engineering standards, tooling, and best practices for both code and research design. * Innovation: Conduct thorough code and design reviews, champion technical innovation, and proactively address technical debt to accelerate the R&D lifecycle. Requirements: * Technical Skills: * Senior Experience: Previous demonstrable role(s) as a Staff, Principal, or Senior Engineer (or equivalent Research Scientist) in a Frontier AI Lab with a proven track record of leading complex, end-to-end AI/ML projects from conception to production. * Education / Publication: Preferably PhD (or equivalent research experience) in Machine Learning, Computer Science, or a related field, preferably with a strong publication record (e.g., NeurIPS, ICML, ICLR) in Computer Science. * Core Expertise: Deep theoretical and practical expertise in Agentic AI and proven experience building, scaling, and shipping solutions involving foundation models (LLMs/VLMs). * Soft Skills: * Collaborative: Enjoys collaboration and thrives in a teamwork-oriented, fast-paced research environment. * High-Impact Communicator: Possesses impactful communication skills, with the ability to bridge the gap between research and engineering and articulate complex ideas clearly. * Mission-Driven: Genuinely eager to explore and solve the new engineering and research challenges at the frontier of agentic AI. * Bonus Skills: * Practical experience applying Reinforcement Learning to systems built on Large Language Models (LLMs). * Experience with distributed systems or cloud computing, preferably in AWS. * Familiarity with building complex simulation environments for agent training. * Experience with LLM training or fine-tuning. * Experience developing large-scale evaluation and benchmarking systems for AI models. * Experience in an agentic framework (e.g., LangChain, AutoGen, CrewAI, OpenAI SDK). * Expertise in system architecture, instrumentation, observability, and monitoring for complex, high-performance 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, 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.