Principal Robotic Simulation Engineer
Ireland, Limerick
Analog Devices
Analog Devices is a global leader in the design and manufacturing of analog, mixed signal, and DSP integrated circuits to help solve the toughest engineering challenges.About Analog Devices
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, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).
Principal Robotic Simulation Engineer
The Dexterous AI Group (DAG) is looking for a Principal Robotic Simulation Engineer to lead the development of advanced physical simulations of complex robotic tasks and industrial environments. These simulations serve as the foundation for enabling cutting-edge AI robotics technologies, designed to achieve a level of generality and dexterity beyond the reach of traditional algorithms and system innovations.
Responsibilities include
- Build high-fidelity, scalable simulations of robotic systems and industrial processes using advanced simulation tools and frameworks.
- Create environments for training AI models in physics-rich, realistic, and diverse scenarios to enhance the dexterity and generality of robotic systems.
- Work with AI researchers, roboticists, and hardware engineers to ensure seamless integration between simulation and real-world deployment.
- Develop tools for simulation automation, domain randomization, data generation, and performance optimization to support large-scale AI training pipelines.
- Provide technical leadership and mentorship to junior team members, fostering a collaborative and innovative work environment.
Qualifications
- Master’s or Ph.D. in Robotics, Computer Science, Mechanical Engineering, or related field, with a strong focus on physical simulation and robotics.
- 8+ years of industry experience in robotics, simulation, or related areas.
- Expertise in robotic simulation tools such as IsaacSim, MuJoCo or similar
- Expertise in finite-element analysis and physics engine such as NVIDIA PhysX
- Strong background in machine learning and robotics, and experience in:
- Strong programming skills in Python and C++ with experience in developing simulation and control systems.
- Deep understanding of kinematics, dynamics, and control systems for robotic systems.
- Familiarity with machine learning frameworks and their integration with simulation environments.
- Experience with multi-robot systems and/or human-robot interaction, large-scale cloud-based simulation is preferred
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For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.
Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.
Job Req Type: ExperiencedRequired Travel: Yes, 10% of the time
Shift Type: 1st Shift/Days
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Computer Science Engineering Industrial Machine Learning Physics Pipelines Python Robotics Security
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