About Metamorphic
Metamorphic is developing new approaches to intelligence by combining machine learning with large-scale experimental neuroscience, informed by the principles that make the brain efficient, flexible, and robust. We are building foundation models trained on rich, continuous neural data — a high-resolution digital twin of the brain at a scale never before possible.
Our founding team spans machine learning, neuroscience, and neurotechnology, with prior work including the MICrONS project, Neuropixels, and the Enigma project, as well as foundational scientific contributions in AI, neural computation, and embodied intelligence. Our work sits at the frontier of AI research, and we believe the highest-impact discoveries will come from researchers and engineers working as a single, tightly collaborative team.
The name Metamorphic reflects our belief that the next advances in intelligence will come from a change in form, beyond scale — from artificial to natural intelligence.
About the Role
A core part of our mission is bringing our neuro-aligned models into the physical world. We are hiring a robotics engineer to advance this mission. You will own the end-to-end loop that takes a policy from simulation onto physical hardware and back again: integrating and maintaining physics simulators, building and operating teleoperation rigs for demonstration collection, bringing up and maintaining real robot platforms, and ensuring our software stack, drivers, calibration pipelines, and data recording infrastructure are reliable enough for both rapid iteration and reproducible experiments.
This role sits at the intersection of robotics engineering, scientific infrastructure, and applied research. You will have substantial autonomy over how our simulation environments, hardware integrations, and teleoperation workflows are designed and evolved as our research scales from single-arm tabletop manipulation toward bimanual and humanoid platforms.
You'll thrive in this role if you:
Are excited about working in a fast-paced, production-focused research lab that often requires switching between simulation, hardware, and software work in the same day
Have strong systems and software engineering instincts and can move quickly without sacrificing rigor or safety around physical equipment
Are comfortable debugging across the full stack — from URDFs and controller gains to ROS nodes, GPU drivers, and Python deployment code
Enjoy pair programming and deeply collaborative work, including hands-on time in the lab with researchers and hardware engineers
Are eager to learn more about machine learning research and neuroscience in a novel scientific domain
Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research
Have ambitious goals for AI progress and are excited to create the best outcomes over the long term
We offer:
The chance to work on one of the most scientifically consequential AI projects being pursued today, at the point where it touches the physical world
A small, world-class team where your contributions directly shape the science and the company
Competitive compensation and benefits, along with visa sponsorship
Strong mentorship and career development
Salary Range
$175,000 - $250,000 USD
Based on experience. We additionally offer a competitive equity package and comprehensive benefits, as well as visa sponsorship for international candidates.
Minimum Qualifications
Bachelor's degree or equivalent experience in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field
Strong software engineering skills and strong working proficiency in Python; comfort with C++ for real-time and driver-level work
Hands-on experience operating, debugging, and developing robotics simulation pipelines
Hands-on experience bringing up and operating real robot hardware including end-effector integration, calibration, and safety procedures
Working knowledge of the ROS/ROS 2 stack, including writing and debugging nodes, working with TF, message types, launch files, and integrating sensors (RGB-D cameras, force/torque sensors, IMUs)
Experience collecting, recording, and validating robot trajectory data, including handling synchronization across cameras, proprioception, and action streams
Comfort working closely with ML researchers to deploy and evaluate policies, diagnose sim-to-real gaps, and iterate on the integration between models, environment, and hardware
Nice to Have
Experience designing and operating teleoperation systems
Familiarity with sim-to-real transfer techniques
Ability to read and debug GPU code when diagnosing performance issues in simulators or inference stacks
Experience with motion planning, inverse kinematics, and classical control stacks
Familiarity with containerization and reproducible environments for robotics workloads
Background in computer vision, particularly multi-view geometry, camera calibration, and 3D scene representation
We encourage you to apply even if you do not believe you meet every single qualification. If you don't see a role that fits, we encourage you to submit a general application and tell us how you'd like to contribute to our mission.
