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1 день назад

Research Scientist/Research Engineer, Reinforcement Learning

200 000 - 350 000$
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
UK/US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Research Scientist/Research Engineer, Reinforcement Learning (Reinforcement Learning/ML): Building and deploying reinforcement learning systems for financial-market trading with an accent on policy architectures, reward formulations, and rigorous out-of-sample evaluation. Focus on modeling market microstructure, fill dynamics, liquidity, and latency while processing large-scale market data and integrating alpha signals into production trading systems.

Location: Chicago, New York, or London

Annual base salary: $200,000–$350,000 USD

Company

hirify.global develops research-driven technology for global financial markets, including machine-learning-powered trading systems.

What you will do

  • Conduct original reinforcement learning research for financial-market decision-making and trading.
  • Design and evaluate policy architectures, reward formulations, and objective horizons using rigorous out-of-sample benchmarking.
  • Partner with trading and research teams to source, integrate, and validate alpha signals within reinforcement learning frameworks.
  • Model market microstructure, fill dynamics, liquidity, and latency to ensure simulation fidelity against live trading.
  • Build tooling to store, process, and analyze large volumes of market and signal data.
  • Communicate research findings to technical and trading audiences and take methods from research into production.

Requirements

  • 5+ years of experience developing reinforcement learning and/or deep learning systems with measurable impact in industry or academia.
  • Deep expertise in reinforcement learning, including reward formulation, policy architecture, evaluation, and production deployment.
  • Proficiency in Python and/or C++.
  • Familiarity with PyTorch, TensorFlow, and/or JAX.
  • Strong foundation in mathematics and statistics, plus a PhD or Master's degree in Computer Science, Machine Learning, Robotics, or a related field.
  • Strong publication record at ICML, ICLR, AAAI, NeurIPS, CVPR, or an equivalent venue; excellent written and verbal communication skills in English.

Culture & Benefits

  • Collaborative, team-oriented research environment focused on innovation and challenging technical problems.
  • Discretionary bonus eligibility.
  • Medical, dental, and vision insurance, with HSA, FSA, and dependent-care options.
  • Paid vacation, holidays, parental leave, and wellness programs.
  • Retirement plan with employer match and employer-paid group term life and AD&D insurance.

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