Research Engineer Intern
Core
Design, train, and evaluate LLM-centric systems, blending implementation, experimentation, and benchmarking to support algorithmic discovery.
Role type
Research Engineer Intern (LLM systems)
Builds
Scalable experimentation foundations, prompt and code-selection tooling, optimized inference infrastructure
Domain
Generative AI, Algorithmic Discovery, Large Language Models
Deliverable
production ML models
Required skills
Python, PyTorch, JAX, LLM inference and fine-tuning, applied research engineering, evaluation frameworks, unit/property-based testing, performance profiling
Preferred skills
Open research contributions, algorithm design, reinforcement learning, evolutionary methods, optimization methods
Responsibilities
Support development of scalable experimentation foundations with reproducibility and observability; Create and improve robust prompt and code-selection tooling; Optimize system inference and infrastructure for efficiency; Implement new ideas with ML engineers and researchers; Engage with the research community to advance algorithmic discovery
Seniority
Intern