Senior Applied Scientist

Responsibilities

• AI Strategy & Leadership

  • Develop and execute the strategy for LLM evaluation and finetuning for mobile scenarios, balancing quality, cost, speed, and power/resource constraints.
  • Champion the use of SLMs and custom-tuned models to deliver efficient and reliable performance on mobile devices.

  LLM & Prompt Evaluation

  • Design and lead experiments that assess the performance, effectiveness, and safety of language models and prompts in mobile contexts.
  • Leverage synthetic and user-generated data to continuously improve prompt quality and user experience.

  Mobile-Centric AI Experiences

  • Partner with UX, product, and engineering teams to optimize AI workflows for mobile-specific use cases (e.g., on-device summarization, smart notifications, multimodal interactions).
  • Translate complex scientific insights into product features that enhance real-time communication and collaboration on mobile.

  Program Management & Infrastructure

  • Own and evolve the end-to-end evaluation pipeline, ensuring seamless integration with product development cycles.
  • Develop robust measurement frameworks and dashboards to report on LLM performance, user utility, and business impact.

  Responsible AI

  • Apply Microsoft’s Responsible AI principles to ensure the AI in Teams Mobile is safe, inclusive, transparent, and accountable.
  • Proactively identify and mitigate bias, hallucinations, and privacy risks, especially in mobile-centric experiences.

  Cross-Team Collaboration & Thought Leadership

  • Drive alignment across Microsoft Teams, M365 Copilot, Azure OpenAI, and research partners.
  • Contribute to internal and external research in LLM evaluation, mobile UX, and agentic AI, including publications, white papers, or patents.

Qualifications

Required Qualifications: 

• Bachelor's 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 Master's 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+ year(s) related experience (e.g., statistics, predictive analytics, research)
  • OR equivalent experience.
• Proven experience applying machine learning and LLMs to real-world product scenarios.
• Deep expertise in:
  • Prompt engineering.
  • Finetuning and SLM optimization.
  • Evaluation frameworks for LLM quality, utility, latency, and cost.
  • RAG, agentic workflows, and multi-turn dialogue systems.
• Solid development skills in Python and hands-on experience building ML/AI pipelines.
• Experience leading complex, cross-functional technical programs or research initiatives.
• Strong analytical, problem-solving, and communication skills.
• Demonstrated understanding of Responsible AI principles, especially in privacy-constrained or mobile environments.