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# Machine Learning Research Scientist

- **Company:** Johns Hopkins Applied Physics Laboratory
- **Location:** Washington, DC, United States
- **Experience:** Expert
- **Salary:** $124,800.0 - $208,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Machine Learning, Reinforcement Learning, Information Technology
- **Published:** August 4, 2026
- **Apply:** https://www.careerjet.com/job/register/usa9aa18139290d4e9525fc4b8958c8805

## About the Role

* PhD in Machine Learning, Computer Science, AI, or a closely related field.
 * At least one main-conference publication at ICML, NeurIPS, or ICLR.
 * Strong preference for candidates with two or more publications at those venues.
 * Demonstrated experience conducting original ML research.

Preferred Research Areas

 * Reinforcement Learning.
 * Meta-Learning.
 * Recursive self-improvement.
 * AI for Science, for example weather forecasting, protein modeling, or scientific discovery., Successful candidates will have a proven record of advancing state-of-the-art machine learning through top-tier conference publications and deep expertise in frontier ML research. While rapid sourcing is important, selection prioritizes quality of research contributions. Eligibility
 * Must hold a PhD in a relevant field.
 * Must have at least one main-conference publication at ICML, NeurIPS, or ICLR, with preference for candidates who have two or more such publications.

## Description

Lead algorithmic machine learning research in a short, high-priority pilot that assembles a small group of world-class researchers to produce original, frontier ML results on an accelerated timeline. This role emphasizes algorithmic innovation rather than applied analytics and requires fast turnaround. Key Responsibilities

 * Join a small, focused research team for an initial pilot engagement.
 * Conduct original ML research that advances algorithms and theory rather than only applied analytics.
 * Design experiments, implement prototypes, analyze results, and iterate rapidly.
 * Deliver initial data and results by Monday / Tuesday 27th July.


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