In this role

You will contribute to advanced Embodied AI and Robotics research by developing, integrating, and supporting machine-learning and robotic systems across simulation and physical hardware. You will work on software and test automation infrastructure, develop training and evaluation pipelines, prepare and refine robotic datasets, and help deploy novel algorithms for experimentation. Day to day, you may integrate a new simulation environment or robotic platform into an existing learning framework, adapt software to new APIs, collect and convert demonstrations for model training, and launch fine-tuning and evaluation runs of robotic AI models. This role offers the opportunity to work with an agile research team advancing robotic learning and AI foundation models, with your work directly contributing to research objectives and new capabilities.

Responsibilities

• Fine-tune, enhance, and maintain sophisticated software implementations supporting robotic AI and machine-learning research.
• Architect, design, and implement test automation infrastructure for robotics and AI systems.
• Develop training and evaluation pipelines using Azure Machine Learning.
• Analyze, curate, refine, and transform training datasets for robotic and AI applications.
• Develop tools and infrastructure that enable rapid deployment and evaluation of novel algorithms in simulation and on physical hardware.
• Integrate robotic control and perception stacks with simulation frameworks and robotic platforms.
• Integrate new simulation environments and robotic hardware by adapting server/client software to new APIs.
• Collect, process, and convert robotic demonstrations into formats suitable for model training.
• Launch and manage model fine-tuning and evaluation workflows.
• Troubleshoot, diagnose, and resolve issues across new and legacy production systems.
• Perform unit testing and support the reliability and maintainability of software systems.
• Collaborate in an agile environment to prioritize technical work and deliver measurable progress toward research objectives.
• Create technical documentation and other deliverables supporting research and engineering initiatives.

Required Qualifications

• Master’s degree in Computer Science, Computer Engineering, Robotics, or a related technical field.
• 5–7 years of related professional experience.
• Strong foundation in computer science, including data structures, algorithms, and software design.
• Professional programming experience and strong problem diagnosis and resolution skills.
• Experience working with robotic hardware and/or simulation environments.
• Experience with in-depth troubleshooting and unit testing across new and legacy production systems.
• Experience with machine-learning frameworks such as PyTorch or TensorFlow.
• Ability to develop, debug, and maintain complex software systems.
• Experience working with machine-learning models, training workflows, or AI development pipelines.

Preferred Qualifications

• Experience training or fine-tuning robotic learning models, particularly Vision-Language-Action (VLA) models.
• Experience with diffusion models or reinforcement-learning policies.
• Experience integrating robotic platforms, robotic arms, or other physical robotics systems.
• Experience with robotics simulation environments and simulation-to-hardware workflows.
• Experience with robotic perception and control systems.
• Experience developing ML training, evaluation, and deployment pipelines.
• Experience with Azure Machine Learning.
• Experience preparing, converting, and curating demonstration datasets for robotic model training.
• Experience adapting software frameworks to new robotics or simulation APIs.
• Experience developing automated testing infrastructure for complex AI/robotics systems.
• Familiarity with robotic foundation models and emerging approaches to embodied AI.
• Experience working in an agile research or engineering environment where priorities evolve based on experimental results.

Salary Range