Research Engineer / Scientist, Post-training - Paris
H Company is hiring a Research Engineer / Scientist, Post-training - Paris (France). Level rates it ; you can apply on H Company.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- Some of the work can be done remotely, according to the posting.
- The posting mentions PyTorch, TensorFlow and JAX among its tools and skills.
- H Company has 34 other open roles on Level.
AI in 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 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.
How we rate this
Research Engineer / Scientist, Post-training - Paris 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.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What are the limits of PyTorch that you've run into, and how did you work around them?
- What's a project where you used TensorFlow hands-on?
- 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, NLP, PyTorch, TensorFlow, 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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