Principal Applied Scientist

What you'll do

• Translate cutting-edge research in Generative AI and multimodal models into production-ready AI solutions.
• Design and execute experiments to improve agent planning, memory, grounding, and long-horizon task completion.
• Perform lightweight fine-tuning on multimodal and large multimodal language models to improve reasoning and response quality.
• Architect and implement end-to-end agent workflows that decompose user intent into executable plans and tool calls.
• Build and maintain offline and online evaluation pipelines, including golden datasets and human-in-the-loop frameworks.
• Define task-level metrics for agentic behavior such as success rate, hallucination rate, and safety violations.
• Partner with stakeholders to translate business requirements into technical specifications and research plans.
• Lead design reviews and mentor other scientists to improve applied AI execution and production quality.

What we're looking for

• Bachelor's degree in a relevant field and 8+ years of experience, Master's and 6+ years, or Doctorate and 5+ years of experience.
• Ability to pass the Microsoft Cloud background check.
• PhD in Computer Science, Machine Learning, AI, NLP, or an MS with significant experience delivering production-grade AI systems (preferred).
• 10+ years of hands-on experience applying NLP and/or LLMs to real-world production problems (preferred).
• Proficiency in Python and experience with modern ML frameworks like PyTorch or TensorFlow (preferred).
• Experience building production-grade LLM systems including prompt engineering, RAG, and multi-step reasoning pipelines (preferred).
• Experience building agentic or tool-augmented LLM systems including function calling, planners, and API integration (preferred).
• Experience with parameter-efficient fine-tuning techniques like LoRA for LLMs or multimodal models (preferred).