Principal Applied Scientist

Frontier Tuning is Microsofts AI customization platform that enables enterprises to adapt foundation models to their unique workflows domains and datawhile preserving security privacy and reliability at scale. As we grow Frontier Tuning is becoming a critical pillar for ensuring enterprisespecific capabilities are systematically learned and reflected across Microsoft 365 and beyond.

We are seeking aPrincipal Applied Scientist with strong research and systemsbuilding skills who is excited to push the frontier of largescale model posttraining 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 enterpriseready AI systems.

Posttraining may include reinforcement learning finetuning architectural modification inferencetime control evaluationdriven adaptation or privacypreserving training techniques applied under realworld enterprise deployment constraints.

Ideally candidates will have experience in one or more of the following areas:

• Scalable training systems for RLHF/RLAIF or other posttraining pipelines.

• Scalable inference systems for LLMs.

• Transformer architecture design or efficient adaptation techniques (e.g. LoRA-style methods).

• Inferencetime steering controllability or alignment approaches.

• Privacy-preserving machine learning (e.g. differential privacy or secure training).

• Debugging evaluation or development tooling for foundation models.

• Multimodal model training including language vision or diffusion models.

This position is based at the Redmond campus with 3 days per week work in the office and 2 days per week work from home. Domestic relocation assistance is available.

Microsofts 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.

• Design and develop methods to adapt foundation models (e.g. language diffusion or multimodal models) for enterprisespecific tasks such as document understanding workflow automation or content generation.

• Contribute to one or more aspects of the post-training stack including:

  • Scalability and efficiency of training and inference systems

  • Reinforcement learning or fine-tuning methods

  • Architectural or parameterefficient adaptation techniques

  • Inferencetime steering or controllability approaches

  • Tooling for evaluation debugging or model development

  • Privacy- or securitypreserving training techniques (e.g. differential privacy)

  • Harnesses

• Implement and evaluate adaptation approaches under realworld 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 posttraining 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.

• Document approaches and share best practices to improve organizational capabilities in posttraining and secure deployment of foundation models.

• Support mentorship and onboarding of interns or earlycareer team members as appropriate.

• Bachelors Degree in Statistics Econometrics Computer Science Electrical or Computer Engineering or related field AND 8 years related experience (e.g. statistics predictive analytics research)
  • OR Masters Degree in Statistics Econometrics Computer Science Electrical or Computer Engineering or related field AND 6 years related experience (e.g. statistics predictive analytics research)
  • OR Doctorate in Statistics Econometrics Computer Science Electrical or Computer Engineering or related field AND 5 years related experience (e.g. statistics predictive analytics research)
  • OR equivalent experience.

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.