Machine Learning Research Scientist

Full-timeOn-site
San Mateovia Autoscience CareersPosted Sep 14, 2025
Match with my CV

Technical skills

API developmentData science

About this role

Company Description

At Autoscience Institute, we create AI systems that autonomously conduct AI research. Recently, we announced the first AI agent to autonomously create peer-reviewed literature (ICLR 2025 Workshops). We are passionate about pushing the boundaries of artificial intelligence and contributing to groundbreaking advancements in the field.

Role Description

This is a full-time on-site role for a Machine Learning Research Scientist located in the San Francisco Bay Area.

  • 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.

Qualifications

  • Education: PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Exceptional candidates with strong research contributions are encouraged to apply regardless of formal degree.
  • Research: Publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, etc) or equivalent industry experience at corporate AI research labs (Microsoft, Google, Nvidia, TRI etc).
  • Technical: 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.
  • Curiosity: Passion for accelerating scientific discovery through AI and willingness to explore uncharted directions with minimal supervision.

Before you apply

  • 1Which parts of your CV prove experience with API development and Data science?
  • 2Which recent work examples would make your application stronger for this role?
  • 3What details from the original source listing should you confirm before applying?

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