Research Engineer Intern

• Contributions to open research or community tooling.

• Familiarity with algorithm design, and practical understanding of reinforcement learning, evolutionary methods and optimization methods.

• Masters degree in Computer Science, Engineering, related field, or equivalent experience.

• Strong coding skills in Python and experience with PyTorch/JAX and modern LLM tooling for inference and fine‑tuning.

• Experience in applied research engineering, demonstrated by impactful academic projects or internships in LLMs, search/RL, or compilers/verification.

• Exposure to evaluation frameworks, unit/property‑based testing, and performance profiling.

We offer competitive compensation and a stimulating work environment, with the opportunity to contribute to the future of generative AI.

Outstanding interns may be considered for a full-time Research Engineer position upon completion of the internship.

This role designs, trains, and evaluates LLM‑centric systems. The work blends implementation, experimentation, and benchmarking.

As a Research Engineer Intern you will:

• Support the development of scalable experimentation foundations with strong reproducibility and observability

• Help create and improve robust prompt and code-selection tooling.

• Assist in optimizing our system's inference and infrastructure for better efficiency.

• Work with the team (ML engineers and researchers) to implement new ideas.

• Engage with the research community to advance the state of algorithmic discovery.