At Amazon Robotics, we design advanced robotic systems capable of intelligent perception, learning, and action alongside humans, at massive scale. Our mission is to deploy robots that increase productivity and efficiency across Amazon fulfillment centers while operating safely and robustly in complex, contact-rich environments.
We are seeking an Applied Scientist to develop manipulation controllers for robotic systems operating in contact-rich, uncertain environments. In this role, you will design force-aware control strategies grounded in impedance/admittance frameworks and augment them with data-driven policy learning to achieve robust, adaptive manipulation behaviors. You will combine physics-based modeling, control-theoretic design, and machine learning to build manipulation capabilities that generalize across objects, tasks, and operational conditions.
You will collaborate closely with experts in perception, machine learning, motion planning, controls, and software engineering to deliver solutions that perform reliably on real hardware at production scale. As part of this role, you will study and extend relevant academic and industry research in robot learning and manipulation, prototype and validate learned policies in simulation and on hardware, and transition successful approaches into production systems. Successful candidates demonstrate strong intuition for physical systems, experience applying ML to robotics problems, and the ability to reason about failure modes, edge cases, and deployment constraints in contact-rich manipulation. Clear communication, hands-on experimentation, and a bias toward practical impact are essential.
Key job responsibilities
- Research, design, implement, and evaluate machine learning–based manipulation policies for contact-rich tasks, integrating learning with feedback control, estimation, and motion planning.
- Develop learning frameworks that leverage simulation, real-world data, and hybrid physics- and data-driven models to enable robust agency interaction, grasping, insertion, and object handling.
- Design and execute experiments in simulation and on hardware to train, validate, and stress-test learned manipulation policies under real-world variability and uncertainty.
- Collaborate with software engineering teams to deliver scalable, real-time, and maintainable implementations of learning-based manipulation algorithms in production robotic systems.
- Partner with cross-functional teams across perception, hardware, systems engineering, science, and operations to transition learned policies from research prototypes to reliable, production-ready capabilities across Amazon Robotics platforms.
A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
Basic Qualifications
- PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience designing, running, and analyzing experiments in simulation and on real robotic hardware.
Preferred Qualifications
- Experience developing manipulation policies for contact-rich tasks such as grasping, insertion, force-controlled interaction, or object manipulation.
- Strong foundation in robot dynamics, control, and state estimation, and experience integrating these with data-driven methods.
- Hands-on experience with reinforcement learning, imitation learning, or hybrid learning–control approaches applied to robotics.
- Familiarity with simulation tools and sim-to-real transfer for robotic manipulation.
- Experience collaborating with software engineering teams to transition research prototypes into scalable, real-time production systems.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, MA, North Reading - 142,800.00 - 193,200.00 USD annually