We are the Bing Places team at Microsoft AI organization, and our mission is to empower people and organizations everywhere to discover, navigate, and connect in the physical world. We achieve this by providing exceptional local search and maps experiences to hundreds of millions of users globally.
As an Applied Scientist Manager in our Bing Places Signals team, you will lead the development of efficient solutions to discover and manage reliable signals about our world, helping improve our product user experience. In this role, you will be leading a team of talented scientists to design and implement state-of-the-art machine learning models and algorithms to build the data foundation of the Bing Places product and Copilot. Your work will directly impact millions of users using our product every single day.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Qualifications
Required Qualifications:
* Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research)
o OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research)
o OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research).
o OR equivalent experience.
* Experience with large-scale Machine Learning models and frameworks such as PyTorch.
* Experience with building, deploying, and optimizing large-scale AI/ML models in real-world applications, especially in NLP and Information Retrieval.
Preferred Qualifications:
* Experience working with Large Language models, including fine-tuning and applying performance optimizations for more efficient online inference.
* Experience with Reinforcement Learning systems.
* Background in developing or modifying deep learning algorithms/architectures to improve computational and memory efficiency.
* Experience in search engines or recommendation systems.
* Publications in top-tier conferences like NeurIPS, ICML, CVPR, SIGIR, KDD, ACL, EMNLP, ICLR, WWW, WSDM or similar, demonstrating expertise in advancing the field.
Responsibilities
* Coach and provide strategic direction and technical mentorship to a team of scientists and engineers, fostering a culture of innovation and continuous learning.
* Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to discover and validate signals data coming from multiple different sources.
* Design scalable algorithms for online and offline systems, delivering innovative solutions for content selection and user engagement modeling.
* Drive offline and online experimentation to evaluate model performance to achieve high quality standards.
* Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.
* Stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.
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