Do you want to shape the future of the autonomous enterprise and lead the development of intelligent, agent-first experiences that transform how businesses operate? The Business and Industry Solutions (BIS) team is looking for a Senior Applied Scientist to drive innovation at the intersection of AI, experimentation, and enterprise systems. In this role, you will design and evaluate autonomous agents that deliver measurable improvements in accuracy, latency, and cost-efficiency. You’ll lead rapid experimentation cycles, develop robust evaluation frameworks, and apply advanced techniques like reinforcement learning to enable multi-step reasoning and decision-making. You’ll collaborate across engineering, product, and partner teams to ensure agents are performant, secure, reliable, and extensible—empowering customers and partners to build on our platform. This is your opportunity to influence the next generation of AI-native business applications and deliver real-world impact at scale. The ideal candidate has prior expertise in natural language processing (NLP), with a strong foundation in large language model (LLM) development, evaluation, and fine-tuning. They should have hands-on experience in applying advanced fine-tuning techniques—including instruction tuning, reinforcement learning from human feedback (RLHF), and tool-augmented generation—to build agents capable of multi-step reasoning and decision-making. Familiarity with prompt/context engineering, context-aware orchestration, and integrating LLMs with external tools and APIs is essential. The candidate should be comfortable working in a fast-paced, experimentation-driven environment, leveraging both offline and online evaluation methods to iterate rapidly and optimize agent behavior. A deep understanding of the challenges and opportunities in building AI-native enterprise applications will be key to success in this role.
Responsibilities
- Deliver impactful solutions by executing high‑leverage data science and analytics initiatives within a product area or feature team, ensuring measurable improvements to user and business outcomes.
- Lead the design and implementation of advanced model fine‑tuning pipelines, including Reinforcement Learning from Human Feedback (RLHF), to align AI system behavior with user intent and improve performance in real‑world scenarios.
- Own complex, end‑to‑end projects that combine technical depth with cross‑functional collaboration, influencing feature direction and prioritization rather than broad organizational investment decisions.
- Foster alignment and trust across partner teams through clear, actionable communication and collaborative problem‑solving.
- Develop and maintain robust measurement systems, experimentation frameworks, and causal inference methodologies tailored to dynamic AI systems and enterprise‑scale environments.
- Mentor and support peers by sharing best practices, reviewing designs, and contributing to a collaborative, high‑performance team culture.
- Leverage AI to streamline workflows and enhance team productivity through intelligent automation and innovation.
Qualifications
Required
Qualifications
- Bachelor's Degree in 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 Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Computer Science, Electrical or Computer Engineering, or related field AND 1+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 1+ years of experience with generative AI OR LLM/ML algorithms
Preferred Qualifications
- Experience with MLOps Workflows, including CI/CD, monitoring, and retraining pipelines
- Familiarity with modern LLMOps frameworks (e.g., LangChain, PromptFlow)
- 3+ years of experience publishing in peer-reviewed venues or filing patents .
- Experience presenting at conferences or industry events
- 3+ years of experience conducting research in academic or industry settings
- 1+ year of experience developing and deploying live production systems
- 1+ years of experience working with Generative AI models and ML stacks
- Experience across the product lifecycle from ideation to shipping
Other Requirements
bility 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.
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Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
