AI Research Scientist

Fionics; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

Fionics, based in New York, is hiring AI research scientists to work at the core of its alpha-research process. This is a high-priority build with upstream impact across trading and research platforms.

You will advance foundational ML and reinforcement learning techniques, contribute hands-on engineering work, and collaborate with a team of serious researchers to craft robust models using real market data and scalable infrastructure.

Qualifications

• Strong foundational machine learning across pre-training and post-training.
• Reinforcement learning relevant to financial problems.
• Hands-on and engineering-strong with coding and ML modelling tasks.

Responsibilities

• Contribute to alpha research by developing scalable ML models.
• Collaborate on production-worthy ML systems and data pipelines.
• Explain complex research outputs clearly to stakeholders.

Skills

Foundational ML

Reinforcement Learning

Engineering mindset

Strong communication

Education

PhD preferred

Exceptional non-PhD considered

Tools

Python

TensorFlow

PyTorch

NumPy

Job description

One of the most respected systematic funds in the world is hiring AI research scientists at the core of its alpha-research process. This is a high-priority build, and the work sits upstream of a large part of what the firm does.

Why it's worth a look

• Your research feeds directly into the firm's alpha engine. Genuine leverage, not a side project.
• You sit on an engineering-heavy team of serious people, working on hard problems with real data and real resources behind you.
• A rare seat where deep AI research and financial markets actually meet, so both sides of your skill set get used.

What we're looking for

• Strong foundational machine learning across pre-training and post-training. Reinforcement learning relevant too
• Hands‑on and engineering‑strong. You'll be tested on coding and ML modelling, not just theory
• Strong academic pedigree, PhD generally preferred, though exceptional non-PhD candidates are considered
• Finance experience or a clear, genuine interest in solving financial problems. This matters
• Well-rounded and articulate, able to explain your work clearly

Comp:

among the strongest in the market for the right person.