ML Research Scientist
Role Overview
Conduct empirical research on how models behave when sharing hardware, using the company's own hardware and real fleets.
Turn findings into product and orchestration decisions.
Key Skills for This Role
Full Job Posting
Role overview
Conduct empirical research on how models behave when sharing hardware, using the company's own hardware and real fleets.
Turn findings into product and orchestration decisions.
What you will do
- Design and run experiments on real fleets rather than synthetic proxies.
- Investigate model behaviour under co-location, quantisation, adapter serving, and mixed-precision execution.
- Translate findings into actionable decisions for the orchestration layer and collaborate with engineering to implement them.
- Publish internal research with rigorous methods, data, and stated limitations.
- Track literature and distinguish substantiated results from claims.
What you need
- Doctorate or equivalent research experience in machine learning, systems, or a numerate discipline.
- Experience running experiments end to end, including instrumentation.
- Strong Python skills and comfort reading and modifying model and serving code.
- Discipline to state research limitations clearly.
Useful, not required
- Published work in efficiency, quantisation, serving, or systems for machine learning.
- Experience with adapter methods, distillation, or mixture-of-experts serving.
- Track record of research that shipped.
What the company offers
- Meaningful ownership and impact at an early-stage deep tech company building foundational technology in house.
- Close collaboration with a small, senior team on problems combining hardware, systems, and AI at scale.
Compensation
- Competitive early-stage compensation; no compensation cadence or amount is stated.
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