Principal Applied Science Engineer at Microsoft

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

12 Apr, 26

Salary

0.0

Posted On

12 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Natural Language Processing, Reinforcement Learning, Data Science, Statistics, Predictive Analytics, Model Fine-Tuning, Software Engineering, Cloud Technologies, Experimentation Frameworks, Causal Inference, Large Language Models, Context Engineering, Automation, Collaboration

Industry

Software Development

Description

Overview 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 Drive strategic impact by identifying and leading high-leverage data science and analytics initiatives across multiple product domains. Lead the development and deployment of advanced model fine-tuning pipelines, leveraging Reinforcement Learning from Human Feedback (RLHF) to align AI system behavior with human intent and improve performance in complex, real-world enterprise scenarios. Steer strategic direction and investment decisions by owning complex, end-to-end projects that blend technical depth with organizational influence. Build alignment and trust across leadership and cross-functional teams through clear, persuasive communication and collaborative engagement. Design and implement robust measurement systems, experimentation frameworks, and causal inference methodologies tailored to dynamic AI systems and enterprise-scale environments. Mentor and elevate the data science community by championing best practices, nurturing talent, and cultivating a collaborative, high-performance culture. Harness AI to accelerate workflows and amplify team productivity through intelligent automation and innovation. Qualifications Bachelor's degree in Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) (OR) Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) (OR) Doctorate in Statistics, Mathematics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) 5+ years experience developing and deploying AI/ML products or systems at multiple points in the product cycle from ideation to shipping. Preferred Qualifications: Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research) (OR) Doctorate in Statistics, Mathematics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) 5+ years experience developing and deploying GenAI products or systems at multiple points in the product cycle from ideation to shipping. Experience with modern NLP techniques and language model architectures (e.g. Transformer, etc). Deep understanding of statistics and statistical theory Experience working with real-world noisy data Demonstratable experience with software engineering principles, parallel and distributed computing, statistics, machine learning, cloud technologies like Azure, AWS, Google Cloud, IaaS, PaaS and SaaS Other Requirements Ability 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. #BICJobs This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

Drive strategic impact by leading data science and analytics initiatives and developing advanced model fine-tuning pipelines. Collaborate across teams to design robust measurement systems and mentor the data science community.