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

We're looking for an Applied AI Engineer to join the team responsible for building Edison's most powerful AI agents. Half of the public agents on our platform, including Kosmos, our flagship product, came directly out of this team.

You'll own the development and maintenance of production agents, prototype new capabilities with our internal science and engineering teams, and shape how our platform evolves. You'll spend some time with customers to understand real workflows and validate what you're building, but your primary focus is on the agents themselves – making them more capable, more reliable, and more useful across the life sciences.

Responsibilities

• Architect, implement, and maintain the AI agents that power Edison's platform, from prototype through production.
• Work with our internal science and engineering teams to explore new agent architectures, prompting strategies, tool integrations, and evaluation frameworks.
• Develop reusable infrastructure – agent skills, tool-use pipelines, benchmarks – that improves every agent on the platform.
• Spend time with R&D partners (~30%) to understand their workflows, test what you've built in real environments, and bring insights back to the team.
• Translate field insights and internal research into product direction – help the team prioritize what to build next.

Qualifications

• 3+ years of professional software engineering experience, with production experience shipping systems that real users depend on.
• Experience building LLM-powered tools or applications: prompting, context engineering, agent architectures, evaluation frameworks.
• Strong engineering foundation in Computer Science, Software Engineering, Mathematics, Physics, Data Science, or a related technical field.
• Proficiency in Python and/or TypeScript, with comfort picking up new tools and frameworks quickly.
• Able to work across engineering, science, and product teams.
• Comfortable building from scratch, driving clarity in ambiguous situations, and wearing multiple hats.

Bonus points for:

• Experience in life sciences, biomedical research, scientific computing, or technical R&D workflows.
• Experience building agent systems, tool-use pipelines, or evaluation/benchmarking frameworks for AI applications.
• Contributions to open-source scientific or AI tooling.

Salary

$160,000 - $280,000  •  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

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

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 a Principal Machine Learning Engineer at Edison Scientific, you play a central role in building the models and agents that accelerate scientific discovery. You will work on both cutting edge research and practical engineering, bridging advanced machine learning concepts with robust, reliable software that real scientists depend on.

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 qualitative challenges in building AI agents for science as well-formulated optimizable problems
• Build appropriate environments in which to train and deploy AI agents that solve scientific tasks
• Work with scientists to formulate training data pipelines, and scale them, ensuring observability and reproducibility
• Lead training of large-scale LLM-based systems, including building internal infrastructure to improve the efficiency of experimentation and production training runs
• Build efficient and flexible inference infrastructure, supporting complex sampling algorithms and custom architectures
• Develop and extend our experimentation platform for internal tools and projects.
• Collaborate closely with a multidisciplinary team of AI researchers, chemists, biologists, fostering an environment of innovation and discovery.

Qualifications

• 8-10+ years of strong track record of work in applied ML research and application of ML methods to solving real-world problems
• Experience working across the ML lifecycle: data pipelines and provenance, model training, model deployment, and validation in production systems.
• Fluency 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 computing resources
• Background architecting complex distributed systems

Salary

$275,000 - $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