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Machine Learning Researcher (Large-Scale ML / GenAI): Quant Fund
Machine Learning Researcher (Large-Scale ML / GenAI): Quant FundHunter Bond • Miami, FL, US
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Machine Learning Researcher (Large-Scale ML / GenAI) : Quant Fund

Machine Learning Researcher (Large-Scale ML / GenAI) : Quant Fund

Hunter Bond • Miami, FL, US
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  • [job_card.full_time]
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Job Description

We are retained by a stealth, elite quantitative investment firm building a world-class research platform at the intersection of machine learning, generative AI, and quantitative finance. Backed by exceptional capital and leadership, this start-up environment offers the freedom and resources to pursue frontier AI research with real-world deployment.

We are seeking an outstanding Machine Learning Researcher to join a small, highly selective research team.

Role Overview

You will work at the cutting edge of modern AI—designing, training, and scaling state-of-the-art ML and GenAI systems. This is a deeply research-driven role with direct ownership of ambitious problems and access to significant compute and data. This will result in building strategies for trading Equities, Options and Crypto.

Key Responsibilities

  • Train large-scale ML and generative AI systems end-to-end, from raw data processing through fine-tuning and evaluation
  • Develop novel AI / ML architectures, including transformer-based and generative models
  • Train state-of-the-art systems across supervised, unsupervised, and reinforcement learning
  • Explore and curate new datasets to extract novel signal and drive performance
  • Contribute to original research and long-term AI strategy alongside elite researchers

Required Background

  • Proven experience training ML models end-to-end, from data pipelines to fine-tuning
  • Strong hands-on experience across transformers, generative models, and reinforcement learning
  • Publications in top-tier ML venues (e.g., NeurIPS, ICML, ICLR, JMLR, or equivalent)
  • Strong Python
  • PhD / MSc or equivalent research experience from a top-tier academic institution for example (but not limited to) :

  • MIT, Stanford, UC Berkeley, Carnegie Mellon, Princeton, Harvard
  • Oxford, Cambridge, Imperial College London, UCL
  • ETH Zurich, EPFL, Max Planck Institutes, University of Tübingen
  • University of Toronto, Mila (Université de Montréal), Vector Institute
  • Alternatively, elite research experience from leading AI labs or top-tier industry research groups

    Why Join

  • Huge backers - roadmap to $1billion AUM over next 18 months
  • Great bonus and equity potential
  • Work in a low-bureaucracy, high-signal research culture
  • Direct access to exceptional compute, data, and research autonomy
  • Ability to conduct real ML research that goes into production
  • Highly competitive compensation with meaningful upside
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