Research Engineer

Autoscience•Menlo Park, CA

37d•Onsite

About The Position

Leading scientific labs increasingly depend on frontier AI, but access to world-class AI research remains a major bottleneck; Autoscience is addressing this by building autonomous R&D systems that design ML architectures, run experiments, and discover improvements that outperform leading human ML teams. Already improving frontier AI models, Autoscience aims to rapidly advance these systems and give every frontier lab AI researchers that accelerate ML progress and scientific discovery.

Requirements

Excellence in your Harvard coursework in CS, ECE, Math, or a related major. Exceptional candidates with strong research contributions are encouraged to apply regardless of degree program.
Publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, etc) or equivalent internship experience with an AI research lab.
Expertise in training machine learning models, including deep learning, reinforcement learning or genetic algorithms. This does not include building multi-agent systems using LLM APIs or building RAG-based agents.
Passion for accelerating scientific discovery through AI and willingness to explore uncharted directions with minimal supervision.

Nice To Haves

Experience building scalable and production-ready machine learning pipelines or large-scale model training (distributed model training over >64 GPUs).
Any background or proven interested in Automated Scientific Research is a plus.

Responsibilities

Work directly with the founder to develop autonomous research systems that ideate, experiment, and improve customer models.
Collaborate with the engineering team to build and deploy production-ready research systems.
RL post-train and fine-tune reasoning models to automate components of the machine learning research process.
Stay current with the latest developments in AI research and automation.