Deep Understanding: When training produces results that don't make sense, you dig until you understand why. The goal isn't just to fix it; it's to carry that understanding forward to the next problem.
Alignment and Agent Behavior: Apply and advance techniques like RLHF, RLAIF, and constitutional approaches to shape how agents reason, act, and collaborate with humans in long-horizon tasks.
Scaling and Exploration: Measure how performance scales with data and compute, and develop new methodologies when existing ones hit ceilings. We expect both rigor and invention.
EXCEPTIONAL CANDIDATES HAVE DEMONSTRATED
A track record of advancing ML systems through post-training, alignment, or related methods: RLHF, RLAIF, preference modeling, reward learning, or equivalent
Strong fundamentals in probability, statistics, and ML theory. The ability to look at experimental data and distinguish real effects from noise and bugs
Evidence of original contributions: publications at top venues, open-source impact, or equivalent industry results
Experience with large-scale distributed training and the debugging that comes with it
Systems-level thinking: not just model optimization, but understanding how training pipelines, data, and evaluation interact
Comfort with ambiguity and fast-moving research environments where priorities shift quickly
We care more about demonstrated capability than credentials. A PhD is one signal among many.
RESOURCES & ENVIRONMENT
Small, highly selective team where research and product move together; prototypes reach real deployment quickly
Compute is not a constraint: large allocations with training jobs routinely running across thousands of GPUs from day one
The environment rewards speed, autonomy, and technical depth with minimal process overhead; this is one of the most competitive and fast-moving problems in AI
Everything needed to operate at frontier scale from day one.
OUR COMMITMENT
Equal Opportunity. Cognition is an equal opportunity employer. We do not discriminate on the basis of any protected characteristic under applicable law. We are committed to providing reasonable accommodations for candidates with disabilities throughout the hiring process - please let us know if you need any. Cognition also considers applicants with criminal histories consistent with the SF Fair Chance Ordinance and similar local laws.
Data Privacy and Arbitration: By submitting your application, you agree to our Global Applicant and Job Candidate Privacy Notice https://cognition.com/documents/Cognition-Global-Applicant-and-Job-Candidate-Privacy-Notice.pdf. For US applicants, by submitting your application, you agree to the Applicant Arbitration Agreement https://cognition.com/documents/Cognition-Applicant-Arbitration-Agreement.pdf.
