Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience.
Demonstrated coding, debugging, and engineering skills in programming languages such as Python or C++.
Hands-on experience with modern deep learning frameworks (e.g. Pytorch/Tensorflow/Jax).
Self-motivated team-player, problem solver, and keen to learn.
Ability to present complex technical concepts to a diverse audience.
Preferred Qualifications:
A PhD in Robotics, Machine Learning, or a related field, OR 3+ years of relevant industry experience.
Experience in one or more of the following areas:
Foundation Models: hands-on training experience in at least one of the following topics: LLMs; Large vision-language models (VLMs); Video generative models and diffusion algorithms; or action-based transformers and Vision Language Action models (VLAs).
Large-Scale ML Systems: Experience with large scale machine learning compute systems.
Robotics: Hands-on training experience in robot learning techniques, such as reinforcement learning, imitation learning as well as classical control methods
Solid understanding of robot kinematics, dynamics and sensors
Familiarity with control algorithms such as PID, model predictive control (MPC), and whole-body control.
Track record of impact, either via first author research publications at top-tier machine learning or robotics conferences (CoRL, RSS, NeurIPS, ICML, ICLR, CVPR), or via contributions to successful industry initiatives.
What You'll be Doing:
Design and implement novel foundation models and algorithms for general-purpose embodied agents;
Implement high-performance machine-learning pipelines and optimize data and learning stacks for scalability, efficiency, and performance.
Optimize and deploy AI models on robot hardware;
Collaborate across Microsoft research and engineering teams to transition cutting-edge research into real-world impact.
Drive the team's rapid progress, with success measured by both the advancement of internal capabilities and impactful contributions to the scientific community
Opportunity to collaborate with top academic partners like ETH Zurich to advance pioneering research at scale, with opportunities to co-author work in top-tier venues, present at workshops, and mentor students.
Perks and Benefits:
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.