Description
The Bing Places team is building intelligence that powers local search experiences used by millions of people every day. We are looking for Applied Scientists to help design, build, and ship advanced AI and machine learning solutions,spanning large language models (LLMs), retrieval augmented generation (RAG), learning-to-ranking, and entity understanding,to deliver high-quality, trustworthy local search experiences at scale.
As an Applied Scientist on Bing Places, you will work on challenging problems that require deep technical expertise and a strong focus on real-world impact. You will work end-to-end: from problem formulation and data analysis, through model development and experimentation, to production deployment and live flighting. You will collaborate closely with engineering and product partners to develop, experiment with, and ship models that operate at Microsoft scale, while contributing to the broader scientific community through publications and patents.
Key responsibilities include formulating complex product and engineering problems as machine learning and AI tasks, designing, implementing, and evaluating ML- and LLM-based models, conducting rigorous data analysis, and owning experimentation pipelines. You will also partner closely with engineers to integrate models into production systems and ensure long-term reliability and performance.
To succeed in this role, you will need a strong background in machine learning, statistical methods, and data-driven problem-solving, as well as hands-on experience developing and evaluating models on large-scale, real-world datasets. Proficiency in Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX is also required. Additionally, you should have a proven track record of publications or granted/pending patents, and be comfortable operating across the full lifecycle,from research and prototyping to production and live operations.
If you are a motivated and talented individual who is passionate about building intelligent systems that can drive real-world impact, we encourage you to apply for this exciting opportunity.