Machine Learning Researcher (Quant Finance)

Are you a Machine Learning Researcher with deep learning, LLM, or sequence modeling expertise looking to join one of the most sophisticated systematic trading businesses in the world, right here in New York City?

My client, a core pillar of a leading quantitative trading firm, is scaling its research organization and is hiring Machine Learning Researchers to build models across pre-training, post-training, reinforcement learning, time series, and frontier deep learning that get deployed directly into live trading, with no portfolio managers standing between the research and the market.

If you're ready to bring frontier ML research into one of the most collaborative, model-driven trading environments in the industry and are available to move quickly, then this is the role for you.

What's the Job?

My client's quantitative research division is fully systematic and fully automated, there are no portfolio managers and no fundamental or manual traders. Researchers and research engineers build the models, and the deployed models make the money, across all major asset classes and time horizons, from microseconds up to months.

The division operates as one collaborative P&L rather than siloed books or pods: research is shared across teams, everyone pulls their own weight, and individual contribution is measured through year-end performance review rather than carved-out attribution. It's organized into several research teams of roughly 10-20 people each, evenly split between researchers and research engineers, with a majority of those teams focused on ML and deep learning.

As a Machine Learning Researcher, you'll work on problems spanning pre-training, post-training, reinforcement learning, time series and sequence modeling, and large language model / NLP applications, as well as designing models for robustness and scalability and partnering closely with researchers, engineers, and traders.

Compensation

Total compensation is calibrated to impact: offers up to roughly $2M are fair game for strong researchers, $2M-$4M is achievable for a senior researcher who can genuinely move the needle for the business.

Qualifications

• Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Mathematics, Statistics, Engineering, Physics, or a related quantitative field

• Deep expertise in machine learning, deep learning, sequence modeling, and/or large language models

• Hands-on experience with modern techniques such as pre-training, fine-tuning/post-training, and reinforcement learning

• Strong Python skills with proficiency in PyTorch or JAX

• Solid mathematical and statistical foundations

• A proven track record of innovative research applied to practical, high-stakes problems

• Genuine interest in financial markets and price formation, even without prior finance experience

Location

New York City

Who are They?

My client is one of the most prestigious and sophisticated quantitative trading firms in the world, running a fully systematic, technology-driven investment business across every major asset class and time horizon. Their research culture is deliberately collaborative rather than siloed, built around shared research and a single P&L, and they compete aggressively for top-tier ML and deep learning talent alongside the world's leading AI labs.

To learn more, apply here today or email me at: [email protected].