Mechanical Engineer, Manipulation

- Bachelor's degree in mechanical engineering, mechatronics engineering, or equivalent
- 3-5+ years designing mechanical systems for robotics, grippers, end-effectors, or complex electromechanical products
- Proficiency in 3D CAD (SolidWorks, OnShape, or equivalent)
- Hands-on experience building prototypes, integrating hardware, and troubleshooting mechanical issues
- Experience designing compact mechanisms with integrated actuation and sensing
- Experience with rapid prototyping methods (3D printing, CNC, laser cutting, sheet metal)
- Familiarity with actuator/motor selection for compact, force-controlled applications
- Experience with structural analysis and material selection for lightweight, functional parts
- Master's degree in mechanical engineering, mechatronics, or robotics
- Experience designing robotic grippers, end-of-arm tools, or dexterous manipulation hardware
- Familiarity with tactile sensing, force/torque sensing, or compliant mechanism design
- Experience with teleoperation hardware or data collection systems for robot learning
- Exposure to imitation learning, learning from demonstrations, or sim-to-real transfer concepts
- Experience with cable-driven mechanisms, tendon routing, or underactuated hand designs
- Knowledge of DFM/DFA principles for small-batch production
- Experience working in research environments with rapidly evolving requirements
- Basic familiarity with ROS, controls, or embedded systems for integrated design work

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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.
We are seeking a Member of Technical Staff - Mechanical Engineer to design and develop robotic manipulation hardware within a frontier AI and robotics research lab. You will own the mechanical design of manipulation-focused hardware end-to-end: grippers, end-of-arm tooling (EOAT), multi-finger hands, UMI-style grippers, and data collection fixtures - all built to enable AI researchers to collect high-quality demonstration data and validate learned manipulation policies.

This role sits at the intersection of mechanical design and AI research. You will be the person who builds the physical tools that make robot learning possible, rapidly prototyping and iterating on end-effectors and data collection hardware, working hand-in-hand with AI/ML researchers to understand what mechanical properties (compliance, sensing, geometry) actually matter for learned manipulation policies.

The ideal candidate is hands-on, moves quickly, is motivated by learning across domains, and is as comfortable sketching a new gripper concept as they are debugging a real-world manipulation experiment. You thrive in fast-paced R&D environments where requirements evolve quickly, and you are genuinely curious about how your design decisions influence data quality and policy performance. If you want to directly shape the hardware that enables the next generation of robot learning, this role is for you.

What You Bring:
- A hands-on, build-first mindset: comfortable prototyping, testing, and iterating rapidly in a research environment.
- Comfort designing in environments where requirements evolve quickly and hardware needs to be rethought from week to week
- Genuine interest in how mechanical design choices such as compliance, geometry, sensing integration, etc. impact data quality for robot learning
- Familiarity or curiosity about imitation learning, teleoperation, or data collection for manipulation
- A collaborative and communicative working style, especially in multi-disciplinary research environments spanning AI, controls, and perception
- A passion for robotics and advancing the state of the art in dexterous, capable manipulation systems

Key job responsibilities
- Design grippers, end-of-arm tools, and low DoF multi-finger hands for robotic manipulation research and data collection.
- Develop UMI-style grippers and teleoperation hardware for collecting manipulation demonstration data.
- Design fixtures, jigs, and mounting systems for cameras, sensors, and manipulation test setups.
- Integrate tactile sensors, force/torque sensors, and cameras into compact gripper assemblies.
- Rapidly prototype and iterate on manipulation hardware — from concept sketches to functional grippers in days/weeks.
- Partner with AI researchers to understand what mechanical properties (compliance, sensing, geometry) matter for learned manipulation policies.
- Design data collection devices, such as UMI grippers, that enable repeatable, high-quality demonstration capture.
- Conduct mechanical testing of gripper performance (grasp force, compliance, durability, repeatability).
- Apply DFM/DFA to scale successful gripper designs from one-offs to small batches (10s–100s of units).
- Own cable routing, actuation, and sensing integration for compact end-effector designs.
- Support hands-on builds, debug sessions, and real-world manipulation experiments.
- Collaborate with controls, perception, and AI teams to ensure hardware meets research needs.

About the team
Frontier AI & Robotics (FAR) is the team at Amazon building the next generation of embodied intelligence. FAR drives the development and implementation of advanced AI models within Amazon’s operations that enable robots to see, reason, and act on the world around them, supporting a number of different warehouse automation tasks.