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NLP​/AI Engineer

Job in New York, New York County, New York, 10261, USA
Listing for: Point72
Full Time position
Listed on 2026-02-19
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: NLP / AI Engineer
Location: New York

We are seeking a NLP engineer for a NLP research team within Point
72. The ideal candidate has a track record of developing modern NLP solutions, including the use of LLMs, agents, RAG, open-source models fine-tuning and deployment, etc.

Responsibilities include:

  • Exploring and combining rich internal and external textual datasets
  • Building GenAI solutions, leveraging both internal models and external APIs
  • Formulating research hypothesis to derive alpha
  • Post-training models for specific tasks
  • Benchmarking LLM approaches internal tasks

We believe the investment world offers unique opportunities to use modern NLP methods. We are a team ideally situated for that, having access to both internal and commercial datasets, with an end-to-end research philosophy and direct portfolio impact.

Requirements:
  • Bachelor, Master’s or PhD graduate or candidate in computer science or another quantitative discipline
  • Experience in NLP, particularly LLMs.
  • Proficient in Python, SQL and general software engineering principles (github, testing, etc.)
  • Data science stack familiarity
  • Interest in financial markets
About Point
72:

Point
72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent.

We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information,

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