Senior Roboticist

Astera Institute•Emerybille, CA

11d

About The Position

Astera Institute is a private foundation supporting ambitious work in science and technology through grants, investments, and in-house research. Its research programs combine the pace and autonomy of a startup with the freedom to pursue difficult scientific questions. Astera’s Robotics Lab is building a frontier robotics program that brings together neuroscience, AI, and robotics to investigate embodied intelligence. The lab aims to expand the repertoire of behaviors robots can perform reliably in real environments while improving their ability to learn skills, adapt to changing conditions, and recover from failure. Practical robotics capabilities also provide a testbed for investigating how biological neural circuits generate intelligent behavior. As a Senior Roboticist, you will contribute to robotics research and engineering within a multidisciplinary team. You will advance robot capabilities, coordinate technical execution across the robotics stack, and translate research into reliable performance on physical systems. Working with lab leadership, you will turn scientific priorities into concrete programs, help recruit and mentor robotics researchers and engineers, and establish rigorous technical standards. This is a hands-on leadership role in research and/or engineering, requiring deep robotics expertise and the ability to collaborate with AI and neuroscience colleagues.

Requirements

Typically 10 or more years of relevant robotics research and engineering experience, including 5 or more years leading technical teams or substantial robotics programs; exceptional accomplishments may substitute for a specific number of years.
A record of original work and successful delivery on physical robotic systems, supported by research publications, deployed capabilities, or substantial engineering achievements.
Deep expertise in one or more areas of robotics and broad working knowledge across perception, robot learning, simulation, motion planning, control, and deployment.
Demonstrated ability to turn research prototypes into reliable, reproducible robotic capabilities and diagnose failures across software, models, sensing, and hardware.
Experience recruiting and mentoring researchers and engineers, setting technical standards, and coordinating work across specialties.
Strong grounding in modern AI and an interest in understanding and evaluating ideas from computational neuroscience.
A PhD in robotics, computer science, engineering, or a related field, or equivalent research and technical leadership accomplishments.

Nice To Haves

Prior specialization in neuroscience.

Responsibilities

Expand the range of skills robots can perform reliably, improving task success, generalization, learning efficiency, adaptation, and recovery from failure.
Work with lab leadership to translate scientific priorities into coordinated projects across perception, learning, simulation, control, hardware integration, and deployment.
Help define milestones, coordinate technical efforts, and resolve dependencies to deliver reliable robotic capabilities.
Guide work from algorithm development and simulation through real-world deployment, establishing cycles of data collection, training, evaluation, failure analysis, and improvement.
Help recruit robotics researchers and engineers through candidate sourcing, technical evaluation, and onboarding.
Mentor team members and develop their technical judgment and leadership.
Contribute directly to experimental design, algorithms, software, and system architecture; investigate failures and resolve challenges spanning multiple robot components.
Develop reproducible benchmarks and testing practices that measure performance across repeated trials, varied environments, and changing operating conditions, and use results to guide development priorities.
Collaborate with AI and neuroscience specialists to implement and test learning methods and neural circuit models on robots.
Design experiments assessing both practical capability and the computational mechanisms underlying behavior.
Recommend robotic hardware, compute, and tooling investments based on technical needs and expected impact.
Communicate progress, risks, and tradeoffs clearly to lab leadership.