Machine Learning Research Scientist
At a glance
Mid-level AI Research role at Autoscience. Menlo Park · full-time · no salary stated · we estimate $135,000–$232,000 across the United States.
Autoscience has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build autonomous research systems that generate ideas, run experiments and improve customer models
- Work with engineering to create research systems ready for production use
- Train reasoning models with reinforcement learning and fine-tuning to automate parts of machine learning research
- Track new work in AI research and automation
What you bring
- A PhD or equivalent research record in computer science, machine learning, AI or a related area
- Top-tier AI or ML conference publications, or comparable work at a corporate AI research lab
- Strong model-training skills, including deep learning, reinforcement learning or genetic algorithms
- Curiosity about AI-driven scientific discovery and comfort exploring new directions with limited oversight
Who this fits
This suits a research-focused scientist who can work with the founder and engineering team to develop autonomous research tools. The role is full-time and on-site in the San Francisco Bay Area. E-Verify is required.
From the employer
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.
Recommended Qualifications
Systems: Experience building scalable and production-ready machine learning pipelines or large-scale model training (distributed model training over >64 GPUs).
Science: Any background or proven interested in Automated Scientific Research is a plus.
Benefits & Perks
Our comp is competitive against major LLM frontier lab packages
Unlimited PTO and flexible working arrangements
Conference attendance and publication support
Our Culture
We're a team of passionate researchers and engineers working to automate scientific discovery. We believe in the power of AI to accelerate scientific discovery and are committed to responsible AI development
We are an e-verify employer.