The Principal Applied Scientist role within the Foundry Agent Platform organization at Microsoft focuses on integrating advanced AI-driven solutions into the Azure AI ecosystem. The Agent Performance team aims to develop tools for monitoring and optimizing AI agents, ensuring they meet customer needs and performance standards. This position requires collaboration with researchers and engineers to translate scientific advancements into practical applications. The ideal candidate will have a strong background in AI research and a passion for improving agent accuracy and performance.

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience.
• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience.
• Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience.
• 4+ years foundation in machine learning and applied AI techniques, including model evaluation and optimization.
• 3+ years of experience programming in Python.
• 1+ years of experience in fine-tuning and post-training strategies for models in production environments.
• 2+ years of experience with prompt engineering and optimization for large language models or similar AI systems.
• 3+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• 7+ years experience conducting research as part of a research program (in academic or industry settings).
• 5+ years experience developing and deploying live production systems, as part of a product team.
• 7+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.

• Help to shape the direction of Agent Foundry Platform and Agent self-improvement with industry-leading product work.
• Collaborate with and bridge the gaps between researchers to translate applied research into differentiated, production-quality features.
• Bring new technology and approaches, such as Reinforcement Learning from Human Feedback (RLHF), into production.
• Drive negotiations across teams to ensure cutting edge technology is being applied to products in a practical way.
• Leverage and/or construct data and experimentation to rapidly iterate on and refine product opportunities.
• Proactively provide mentorship and coaching to less experienced and mid-level team members.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.