Principal Applied Scientist - Small Language Models at Microsoft

Reading, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

07 Apr, 26

Salary

0.0

Posted On

07 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Applied Research, Product Development, Deep Learning, Python, C++, Pytorch, TensorFlow, Generative Models, Multimodal Models, Neural Processing Units, Model Optimization, Research Publication, Mentoring, Collaboration, Architecture Design, Training Pipelines

Industry

Software Development

Description

Overview Microsoft’s Applied Sciences Group is seeking a visionary and hands-on Principal Applied Scientist to lead research and development in SLM, VLM, multimodal AI, across language, vision and agent workloads. This role is ideal for candidates passionate about building real-world systems that unify visual and textual modalities to power next-generation user experiences across devices and platforms. As a senior member of the team, you will drive innovation across model architecture, training, and deployment, especially for scalable autoregressive models that handle both language, structured text and reasoning tasks. You will also play a key role in converting cutting-edge research into practical applications and experiences for users across the globe. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities Design and prototype unified token-based architectures that treat text and/or image data as sequences for coherent text or multimodal generation. Work on SLMs for tasks such as planning, image captioning, visual question answering, and structured text generation. Build scalable training pipelines for large-scale text datasets. Optimize deep neural networks for deployment on Neural Processing Units (NPUs), GPUs and cloud environments, maximizing efficiency and performance. Collaborate with cross-functional teams to integrate models into Microsoft products and services. Publish research in top-tier venues (NeurIPS, CVPR, ICCV, ICLR) and contribute to the scientific community. Mentor junior scientists and engineers, fostering a collaborative and innovative research environment. Qualifications Required Qualifications: Doctorate in Computer Vision, Machine Learning, or a related field with demonstratable experience in applied research or product development OR Master's degree in Computer Vision, Machine Learning, or a related field with demonstratable experience in applied research or product development OR Bachelor's degree in Computer Vision, Machine Learning, or a related field with demonstratable experience in applied research or product development Strong publication record in top-tier venues (CVPR, ICCV, ECCV, NeurIPS, ICLR, AAAI). Advanced Python or C++ (especially C++11 and newer) experience. Advanced experience in deep learning and its different toolkits, in particular Pytorch or TensorFlow. Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. Demonstrated ability to translate research into real-world applications. Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow, HuggingFace). Hands-on experience with generative models, especially diffusion and transformer-based synthesis. Experience building and training multimodal autoregressive models, Preferred Qualifications: Experience deploying models to production or on-device environments. Experience optimizing models for Neural Processing Units (NPUs) or other hardware accelerators. Knowledge of quantization, pruning, and efficient fine-tuning techniques. Experience with RLHF, proven ability to design, prototype and implement training pipelines for planning and reasoning Strong collaborative skills across cross-functional teams. #W+DJOBS #ASG #AppliedSciencesGroup This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

Design and prototype unified token-based architectures for multimodal generation. Collaborate with cross-functional teams to integrate models into Microsoft products and services.