Senior/Principal AI Research Scientist

<p><strong>About</strong></p> <p>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.</p> <hr> <p><strong>Role</strong></p> <p>As an <strong>Senior/</strong><strong>Principal AI Research Scientist</strong> 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.&nbsp;</p> <p>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.</p> <hr> <p><strong>Responsibilities</strong></p> <ul> <li>Interpret challenges in building AI agents for science as well-formulated statistical problems</li> <li>Conduct research in post-training of LLMs on challenging scientific reasoning tasks, with the goal of exceeding expert human capacity</li> <li>Conduct research in optimal sampling techniques, considering aspects like efficient exploration and quality-diversity</li> <li>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</li> <li>Develop and extend our experimentation platform for internal tools and projects.</li> <li>Collaborate closely with a multidisciplinary team of AI researchers, engineers, biologists, and chemists, fostering an environment of innovation and discovery.</li> </ul> <hr> <p><strong>Qualifications</strong></p> <ul> <li>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</li> <li>Fluency in PyTorch, Jax, or equivalent framework</li> <li>Experience with large-scale training and experimentation technologies (e.g. Ray, verl, Megatron-LM, etc.)</li> <li>Experience working with data and ML systems: EDA, feature engineering, model development, model deployment, and validation in production systems.</li> <li>Familiarity with modeling in PyTorch, Jax or equivalent framework.</li> <li>Demonstrated experience with experimentation in academic or industry settings.</li> <li>Strong programming expertise with the capability to adapt to various technical challenges in the data, ML, and LLM software stack.</li> </ul> <h3><strong>Bonus points for:</strong></h3> <ul> <li>PhD in Machine Learning, Computer Science, or other quantitative field</li> <li>Familiarity with leveraging and managing distributed systems</li> </ul> <hr> <p><strong>Salary</strong></p> <p>$210,000 - $350,000 &nbsp;•&nbsp; Offers equity</p> <hr> <p><strong>Why join us?</strong></p> <ul> <li>Competitive salary and equity</li> <li>Full healthcare coverage — we pay 100% of premiums for you and your dependents</li> <li>Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot</li> <li>401(k) company matching</li> <li>$300 health and wellness benefit</li> <li>Lunch is on us every day you're in the office, and dinner is on us when you're working late</li> <li>Regular team offsites and company events</li> <li>A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it</li> </ul>