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Senior Applied Scientist

Microsoft· Applied Sciences
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Redmond, WA, Mountain View, CA, New York, NY$119.8k - $234.7kFull-timePosted 4d ago

About the role

Frontier Tuning is Microsoft’s AI customization platform enabling enterprises to adapt foundation models to their workflows, domains, and data with security, privacy, and reliability at scale. The role focuses on large-scale post-training and adaptation of foundation models, combining research with scalable infrastructure and tooling for training, evaluation, and secure deployment in enterprise environments.

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.
  • Document approaches and share best practices to improve organizational capabilities in post-training and secure deployment of foundation models.
  • Support mentorship and onboarding of interns or early-career team members as appropriate.

Qualifications

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

Skills

Required:Foundation model post-training and adaptationReinforcement learning or supervised fine‑tuningPython and ML frameworks (e.g., PyTorch)
Nice to have:Transformer / multimodal model architecturesInference-time steering and controllabilityMachine learning systems for scalable training
Last updated Oct 23, 2026. Interested? Apply on the company site.

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