About this role
Join a small, high-priority pilot team to advance algorithmic machine learning research at the frontier. This role focuses on original, publishable algorithmic innovation rather than applied analytics, requiring world-class research ability, rapid delivery, and close collaboration with a compact group of peers.
Key Responsibilities- Conduct original machine learning research that pushes state-of-the-art.
- Deliver initial data and results on an accelerated schedule, aligned with the pilot timeline.
- Work closely with a small team of senior researchers to iterate quickly and maintain high research quality.
- Prioritize algorithmic innovation and rigorous evaluation suited for top-tier conference publication.
- PhD in Machine Learning, Computer Science, Artificial Intelligence, 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 these venues.
- Demonstrated experience conducting original ML research, with evidence of advancing state-of-the-art.
- Reinforcement Learning
- Meta-Learning
- Recursive Self-Improvement
- AI for Science, for example weather forecasting, protein modeling, or scientific discovery
- Priority: Urgent
- Expected initial data/results: Monday / Tuesday 27th July
- This is an initial pilot engagement with an accelerated timeline, requiring fast turnaround.
Successful candidates will have a proven record of advancing machine learning through publications at top-tier conferences, deep expertise in frontier ML research, and the ability to deliver high-quality results quickly. Speed of delivery is important, but quality must be maintained.
Work Terms- Location: Remote
- Employment type: Hourly
- Engagement: Small initial pilot team, accelerated timeline
- 60 - 100 hourly
Candidates must be able to participate remotely and meet the project timeline. No specific work-authorization or sponsorship details were provided in the source materials.