Principal Engineer, AI/ML Software

Analog Devices•Wilmington, MA

1d•Onsite

About The Position

Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, AI, and software technologies into solutions that combat climate change, reliably connect humans and the world, and help drive advancements in automation and robotics, mobility, healthcare, energy and data centers. With revenue of more than $11 billion in FY25, ADI ensures today's innovators stay Ahead of What's Possible. Learn more at www.analog.com and on LinkedIn and X. Principal Robotics Software Engineer The Dexterous AI Group (DAG) is working toward robots with human-level dexterity—the ability to manipulate objects with the versatility and adaptability people bring to everyday tasks. We combine tactile sensing with vision, robot learning, and control to advance that goal. We seek a hands-on Principal Robotics Software Engineer to lead software architecture across robot systems and the infrastructure used to develop, test, and deploy Physical AI. You will set technical direction and remain hands-on while guiding engineers with different experience levels to deliver shared technical milestones. Why this role matters You will own robotic manipulation use cases and define capabilities that demonstrate our solutions’ differentiation. You will lead the software and infrastructure supporting those capabilities across robot data collection and management, simulation and hardware experiments, model training, evaluation, and deployment. Shared tools and interfaces will let researchers compare ideas without rebuilding pipelines or robot integrations for each use case. Measurable success criteria and repeatable demonstrations will give customers and partners evidence of performance and integration requirements, while informing which capabilities merit further product investment.

Requirements

8+ years developing software for robotics, autonomous systems, or embedded systems, including integration with physical hardware.
Track record of delivering substantial software or systems from design into production, including integration, testing, debugging, maintenance, and reliability improvements.
Strong C++ and Python skills, sound software architecture judgment, and hands-on experience with ROS 2 or comparable robotics middleware.
Working knowledge of robot control, including feedback, timing constraints, actuator limits, and safe integration of learned policies with lower-level controllers.
Working understanding of Physical AI infrastructure across data collection, simulation, training, evaluation, and deployment, with hands-on experience in part of that workflow and ability to assess reproducibility, data quality, compute needs, and latency constraints.
Experience owning use cases: translating application needs into capabilities and success criteria, leading implementation and validation, and explaining demonstrated advantages, limitations, and integration requirements.
Experience leading technical delivery without reporting-line authority, including scoping work, coordinating dependencies, mentoring engineers, and communicating decisions and risks across disciplines.
Sound judgment in ambiguous R&D settings: validate assumptions, make decisions with incomplete information, and balance learning speed, maintainability, and delivery commitments.
Bachelor’s degree in computer science, robotics, electrical or mechanical engineering, or a related field, or equivalent practical experience.

Nice To Haves

Robot manipulation, teleoperation, or integration of tactile, vision, and force sensing.
Familiarity with robotic simulation tools such as Isaac Sim or MuJoCo.
Deployment and evaluation of learned robot policies, including reinforcement learning, imitation learning, or vision-language-action models.
ML data pipelines, GPU or distributed compute infrastructure, or edge inference.
Controller design, such as impedance/force control or model-predictive control; real-time or embedded systems development.
Interest in developing people-management skills over time.

Responsibilities

Own manipulation use cases from definition through demonstration.
Define capabilities and measurable success criteria, validate differentiation against agreed baselines, and set the platform architecture and integration priorities needed to deliver.
Turn ambiguous R&D goals into executable plans.
Identify unknowns, use focused experiments to reduce risk, and make and document technical trade-offs as evidence and priorities change.
Lead delivery across engineers with varied experience.
Break milestones into scoped work with clear ownership, dependencies, integration plans, and acceptance criteria; resolve blockers and communicate progress and risks early.
Design, implement, and review core software in C++ and Python.
Evolve the ROS 2-based stack and integrate hardware, sensing, control, simulation, and learned policies through maintainable interfaces.
Bring production-grade engineering to research software.
Establish appropriate automated tests, continuous integration, hardware-in-the-loop validation, observability, and release practices, with measurable reliability and performance targets.
Partner with AI and other software engineers to design data collection and replay, dataset versioning, simulation, training and evaluation workflows, and deployment tooling.
Connect these through shared data formats and reproducible environments across robot and remote compute.
Align software decisions with hardware, controls, and AI constraints.
Address timing, synchronization, bandwidth, failure handling, and safe robot operation; distinguish exploratory prototypes from capabilities ready for sustained use.
Develop the team through design and code reviews, practical coaching, and clear technical documentation.
Facilitate constructive disagreement, adapt communication to the audience, and help engineers deliver independently.