About Grafton Sciences Grafton Sciences is building physical superintelligence — autonomous systems that can experiment, reason, and make discoveries in the physical world. Backed by $42.5M from ARPA-H, we’re designing autonomous laboratories that learn through interaction, not imitation. If you want to help invent the future of discovery itself, this is the place.

About The Role We’re always looking for individuals who bring world-class ability in engineering, science, research, or operations — even if their background doesn’t fit neatly into one of our listed roles.

If you’re exceptional at building intelligent systems, designing robust physical workflows, creating powerful engineering tools, or inventing new ways for AI to interact with the world, we want to hear from you. We hire people who make the entire organization better — technically, creatively, and operationally.

In this role, you’ll define a scope of work that aligns your strengths with the frontier problems we’re solving. You may work across robotics, AI/ML, digital twins, simulation, agent systems, automation, operations, infrastructure, or entirely new domains we haven’t yet explored.

Responsibilities (Examples) Your work may include (but is not limited to):

• Designing new systems or tools that accelerate physical AI and autonomous experimentation.
• Building intelligent agents that reason, plan, and safely control digital and physical tools.
• Developing simulation, optimization, or digital twin models that close the loop between ideas and reality.
• Creating infrastructure that supports high-throughput engineering, data, verification, or ML training.
• Leading transformative projects in robotics, controls, manufacturing, or scientific automation.
• Architecting processes, workflows, or operations that help scale the autonomous lab.
• Owning high-impact problems end-to-end — from conception to deployment.

Qualifications

• Demonstrated excellence in your craft — whether through research, engineering, design, leadership, or creation of novel systems.
• Ability to define problems from first principles and then execute with clarity and rigor.
• Comfort working in fast-moving, interdisciplinary environments.
• A desire to build real systems that work in the physical world and drive measurable impact.