Senior Applied Scientist

Senior Applied Scientist

United States, Washington, Redmond

+2 more

Job description

Company and benefits

Job number

200062864

Date posted

Oct 21, 2026

Work site

3 days / week in-office

Travel

Less than 25%

Profession

Research, Applied, & Data Sciences

Discipline

Applied Sciences

Role type

Individual Contributor

Employment type

Full-Time

Overview

Frontier Tuning is Microsoft’s AI customization platform that enables enterprises to adapt foundation models to their unique workflows, domains, and data—while preserving security, privacy, and reliability at scale. As we grow, Frontier Tuning is becoming a critical pillar for ensuring enterprise‑specific capabilities are systematically learned and reflected across Microsoft 365 and beyond.

We are seeking Senior Applied Scientist with solid research and systems‑building skills who are excited to push the frontier of large‑scale model post‑training and adaptation. This role spans algorithmic innovation as well as the design and development of scalable infrastructure and tooling for training, steering, evaluating, and securely deploying enterprise‑ready AI systems.

Post‑training may include reinforcement learning, fine‑tuning, architectural modification, inference‑time control, evaluation‑driven adaptation, or privacy‑preserving training techniques applied under real‑world enterprise deployment constraints.

We welcome candidates with experience in one or more of the following areas:

• Reinforcement learning or supervised fine‑tuning for foundation models.
• Scalable training systems for RLHF/Reinforcement Learning from AI Feedback or other post‑training pipelines.
• Transformer architecture design or efficient adaptation techniques (e.g., LoRA-style methods).
• Inference‑time steering, controllability, or alignment approaches.
• Debugging, evaluation, or development tooling for foundation models.
• Multimodal model training, including language, vision, or diffusion models.

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 develop methods to adapt foundation models (e.g., language, diffusion, or multimodal models) for enterprise‑specific tasks such as document understanding, workflow automation, or content generation.
• Contribute to one or more aspects of the post-training stack, including:
• Reinforcement learning or fine-tuning methods
• Architectural or parameter‑efficient adaptation techniques
• Inference‑time steering or controllability approaches
• Tooling for evaluation, debugging, or model development
• Harnesses
• Implement and evaluate adaptation approaches under real‑world enterprise deployment constraints such as latency, safety, privacy, policy compliance, and compute efficiency.
• Partner with research and engineering teams to translate product or customer requirements into scalable model adaptation solutions.
• Explore post‑training techniques that improve domain specialization, tool use, planning, or agentic behaviors in enterprise environments.
• Drive technical work from concept to prototype, delivering new methods, systems components, or empirical insights that advance enterprise model customization.