Skip to content

Open nowPosted 206 days ago

Research Engineer / Scientist, Post-training & Reinforcement Learning - London

H Company34 open roles

Where
Hybrid London
Work mode
Hybrid
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowResearch Engineer / Scientist, Post-training & Reinforcement Learning - LondonH Company · Hybrid London
  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on H Company's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.5% of postings close within 7 days. Measured by our own scanner across the market. H Company postings stay open a median of 24 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.6%3 days
  3. 13.5%7 days
  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: posted 206 days ago

H Company median: 24 days open

The posting

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 RESEARCH & MODELS 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 own the entire pipeline including synthetic data generation, environment design, mid-training, supervised fine-tuning, offline reinforcement learning, online reinforcement learning, reward modelling, transition modelling, etc. Our team also has dedicated MLOps, Infra and Inference support at scale. We focus on improving the long horizon, goal-conditioned instruction-following of large models for GUI/Computer Use agentic interactions, tool use in complex dynamic environments. We regularly ship releases that establish new SOTA in public leaderboards. We parallely 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 us and shape the future of superintelligent AI. Check some of our output

- https://hcompany.ai/holo3

- https://hcompany.ai/holotron3

- https://hcompany.ai/h-joins-nemotron-coalition

- https://hcompany.ai/meet-holotab

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

ABOUT YOU:

You have a strong research engineer / scientist mindset with experience training and improving large language models at different scales in distributed computing settings whether that’s modelling, data collection, experimenting and ablating, implementing SOTA.

TECHNICAL SKILLS:

- You have strong programming skills in Python, Rust, or similar; and strong software engineering fundamentals building performant and reliable systems.

- Proficient in deep learning frameworks (Pytorch, JAX, TensorFlow).

- You can work on different layers of the stack from low-level training backends, data ingestion to ML/RL algorithmic design and implementation.

- You know when and where to be rigorous and slower versus when to break and iterate quickly.

- You have trained LLMs/VLMs with techniques such as SFT, DPO, RLHF/RLVR, reward modelling, offline RL, distillation, etc.

- You have experience with offline and online reinforcement learning in or outside of the context of language models.

PREFERRED:

- Publications in top-tier AI conferences (e.g., NeurIPS, ICML, CVPR, ACL, ICCV, AAMAS, ...)

- Advanced degree (PhD or MSc) in a relevant field (e.g., ML, DL, NLP, CV)

- Experience with large-scale distributed training and inference (multi-node, large models, MoE, parallelism strategies, etc)

- Experience training models for computer use or other multi-turn and/or multimodal agentic settings.

- Extensive experience with reinforcement learning with sparse rewards.

- Experience with multi-domain training, data mixture design, curriculum learning, model merging, distillation.

SOFT SKILLS:

- You are a good communicator, collaborative and low-ego.

- You are able to handle a controlled-chaotic environment with a high-degree of between-teams dependencies and collaboration.

- You have a go-do attitude and can balance personal conviction/interests with wider team needs.

- You don't shy away from hard research or engineering problems.

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 highly competitive salary.

- Unlock opportunities for professional growth, continuous learning, and career development

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

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against H Company's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.
  3. We apply on H Company's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.
  4. Every reply, sorted

    H Company's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.
  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.