Senior/Principal AI Research Scientist

Reposted 9 Days Ago
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San Francisco, CA, USA
In-Office
185K-275K Annually
Mid level
Artificial Intelligence • Software • Database
The Role
Develop models and algorithms to enhance scientific research using AI agents. Collaborate with a multidisciplinary team and manage research projects end-to-end.
Summary Generated by Built In

About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

As an Senior/Principal AI Research Scientist at Edison Scientific, you play a central role in developing the models and algorithms that accelerate scientific research. Your role will encompass both cutting-edge research and applied methods, bringing your work to bear on scientific challenges in laboratories and scientists around the world. 

This role is on-site at our San Francisco office in the Dogpatch neighborhood. Our office is a converted warehouse with high ceilings, open space, and a team excited about what we’re building.

Responsibilities

  • Interpret challenges in building AI agents for science as well-formulated statistical problems
  • Conduct research in post-training of LLMs on challenging scientific reasoning tasks, with the goal of exceeding expert human capacity
  • Conduct research in optimal sampling techniques, considering aspects like efficient exploration and quality-diversity
  • Own research projects end-to-end, from working with scientists to scope the problem all the way to working with engineers to deploy the outcomes
  • Develop and extend our experimentation platform for internal tools and projects.
  • Collaborate closely with a multidisciplinary team of AI researchers, engineers, biologists, and chemists, fostering an environment of innovation and discovery.

Qualifications

  • 6-10+ years of strong track record of ML research on real-world problems in (but not limited to) reinforcement learning, representation learning, and Bayesian methods
  • Fluency in PyTorch, Jax, or equivalent framework
  • Experience with large-scale training and experimentation technologies (e.g. Ray, verl, Megatron-LM, etc.)
  • Experience working with data and ML systems: EDA, feature engineering, model development, model deployment, and validation in production systems.
  • Familiarity with modeling in PyTorch, Jax or equivalent framework.
  • Demonstrated experience with experimentation in academic or industry settings.
  • Strong programming expertise with the capability to adapt to various technical challenges in the data, ML, and LLM software stack.
Bonus points for:
  • PhD in Machine Learning, Computer Science, or other quantitative field
  • Familiarity with leveraging and managing distributed systems

Salary

$210,000 - $350,000  •  Offers equity

Why join us?

  • Competitive salary and equity
  • Full healthcare coverage — we pay 100% of premiums for you and your dependents
  • Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
  • 401(k) company matching
  • $300 health and wellness benefit
  • Lunch is on us every day you're in the office, and dinner is on us when you're working late
  • Regular team offsites and company events
  • A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it
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The Company
HQ: San Francisco, California
47 Employees
Year Founded: 2025

What We Do

Spun out from FutureHouse in 2025, Edison Scientific accelerates discovery and innovation across the sciences. Our platform empowers researchers to move from question to breakthrough faster than ever, automating literature synthesis, data analysis, and molecular design. At its core is Kosmos, our AI scientist, capable of running hundreds of research tasks in parallel. It transforms raw datasets into comprehensive, validated reports—compressing months of work into a single run. With Edison Scientific, scientists remain in control, using AI to amplify their expertise and accelerate discovery at unprecedented speed.

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