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Über diese AI Researcher, LLMs Stelle bei Hudson River Trading

Hudson River Trading · Vor Ort · London, United Kingdom; New York, NY, United States

Hudson River Trading (HRT) is seeking an LLM-focused AI Researcher to join the HAIL team. HAIL (HRT AI Labs) is the team at HRT responsible for developing and maintaining our most powerful AI models, which are used by our trading teams to drive a significant fraction of our trading. The LLM team within HAIL builds large language models from scratch — pretraining, post-training, and serving — that are deployed across the firm to accelerate research, engineering, and trading workflows. Our goal is to produce LLMs that are genuinely best-in-world for the use cases we care about.

In this role, you'll work on every stage of the model development loop: tokenizer training, dataset curation and mixing, pretraining, post-training, evaluation design, inference, and live trading. HAIL researchers have great independence to pursue the directions they think would be most impactful as part of a small, focused team with minimal bureaucracy. They are enabled by state-of-the-art research clusters with very high GPU-to-researcher ratios, and supported by excellent engineering, hardware, and systems teams to realize their vision.

The work is challenging and visibly impactful, and the bar is high: we are not looking for people who will adapt existing recipes. We want people who can drive frontier capability gains and ship the code that gets us there.

Qualifications

  • Two or more years of hands-on experience training, post-training, or evaluating LLMs at scale
  • Direct experience with at least one of: large-scale pretraining, post-training (SFT, RL), LLM evaluation design and statistical analysis, or distributed training/inference systems
  • Research taste: ability to identify what's worth trying next, design ablations that change decisions, and update beliefs from evidence
  • Strong engineering skills valued: GPU kernel development, lower-level PyTorch internals, or published work on a frontier-style LLM result

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package. 

Culture

Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.

At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.

Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is valued. HRT is proud of our diverse staff; we have offices all over the globe and benefit from our varied and unique perspectives. HRT is an equal opportunity employer; so whoever you are we’d love to get to know you.

Please be advised: Use of AI tools by an applicant during interviews or assessments is strictly prohibited, unless otherwise instructed or agreed upon. We employ various methods to evaluate the authenticity of candidate responses. If we determine that AI assistance was used by an applicant during an interview or an assessment, we reserve the right to immediately end the interview or assessment, disqualify the applicant’s candidacy and/or rescind any job offers extended.

You can review our Global Applicant Privacy Notice, which explains how we process applicant information.

 

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