Microsoft Applied Scientist - Multimodal Foundation Models & Robotics 

Taiwan, Taoyuan City 

282565111

Required Qualifications:
• A PhD in Robotics, Machine Learning, or a related field, OR 3+ years of relevant industry 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.
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:
o Hands-on training experience in robot learning techniques, such as reinforcement learning, imitation learning as well as classical control methods
o Solid understanding of robot kinematics, dynamics and sensors
o Familiarity with control algorithms such as PID, model predictive control (MPC), and whole-body control.

• 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.