Research Engineer
Core
Design, train, and evaluate LLM-centric systems for an AI discovery engine that automatically writes algorithms for critical optimization problems.
Role type
Research Engineer (LLM systems & algorithmic discovery)
Builds
Scalable experimentation foundations, prompt/code-selection tooling, optimized inference infrastructure
Domain
Generative AI, Algorithmic Discovery, Optimization
Deliverable
production ML models
Required skills
Python, PyTorch, JAX, LLM inference, fine-tuning, system optimization, evaluation frameworks, unit/property-based testing, performance profiling
Preferred skills
Open research contributions, algorithm design, reinforcement learning, evolutionary methods, optimization methods
Technologies
PyTorch, JAX, LLM tooling
Responsibilities
Build scalable experimentation foundations with reproducibility and observability; Create robust prompt and code-selection tooling; Optimize system inference and infrastructure; Collaborate with ML engineers and researchers to implement new ideas; Engage with the research community to advance algorithmic discovery
Seniority
Mid-level, hands-on IC
