Applied RL Researcher - Open Finance (Remote) & Equity

Prime Intellect, Inc.; New York (NY); Remote; USD 150.000 - 300.000; Vollzeit

Benefits dieser Stelle

Equity incentives

Flexible work location

Professional development budget

Zusammenfassung

Prime Intellect, Inc. is seeking an Applied Research Scientist focused on reinforcement learning, agents, and post-training systems in quantitative finance.

You will build environments, evaluations, and production loops for high-stakes decision making, working with customers and research partners to drive impactful results. You should have deep RL experience, strong Python skills, and a track record in designing experiments, baselines, and robust evidence that informs direction and deployment

Qualifikationen

• We seek depth in RL, agents, or post-training systems and the ability to work fluently in quantitative research.
• Experience in systematic trading, market microstructure, time-series modeling, econometrics, or financial simulation is helpful but not required.
• Hands-on experience building and debugging model-training, post-training, agent, evaluation loops.

Aufgaben

• Applied Research: turn workflows into tasks, environments, evaluations, and reward signals; run post-training experiments against baselines.
• Externally facing role: work with customers, users, or research partners while maintaining a research agenda.
• Owns environments grounded in point-in-time data, realistic market mechanics, and operational constraints.
• Develops verifiers and evaluations for robust out-of-sample behavior across assets, horizons, regimes, and conditions.

Kenntnisse

Reinforcement Learning

Agent-based systems

Python programming

Experimental design

Quantitative research

Tools

Model-training pipelines

Post-training systems

Backtesting

Jobbeschreibung

Prime Intellect, Inc. is seeking an Applied Research Scientist focused on reinforcement learning, agents, and post-training systems in quantitative finance.

You will build environments, evaluations, and production loops for high-stakes decision making, working with customers and research partners to drive impactful results. You should have deep RL experience, strong Python skills, and a track record in designing experiments, baselines, and robust evidence that informs direction and deployment