Applied Scientist

Microsoft•Redmond, WA

1d•$102,100 - $219,200

About The Position

The Copilot Search Multimedia Index Selection team is looking for a Data and Applied Scientist II to help build the next generation platform for Bing and Microsoft AI. Our mission is to construct the most comprehensive, rich, clean, diverse, and fresh image index that serves as the foundation for image-related experiences across Microsoft. We develop advanced AI and machine learning solutions for image content discovery, selection, ranking, and processing to improve the quality and relevance of our multimedia products. Maintaining a comprehensive, diverse, and up-to-date image index presents unique technical challenges. We continuously innovate to improve quality, scalability, and efficiency while supporting billions of images and balancing performance, freshness, cost, and latency requirements. Some of the key challenges you will work on include: Image Content Discovery: Developing approaches to efficiently discover and understand image content across the web. Machine Learning for Selection and Ranking: Building, training, and evaluating machine learning, deep learning, and multimodal models for content understanding, selection, and ranking using both text and image signals. Freshness and Real-Time Systems: Contributing to data pipelines and models that support near real-time indexing and content freshness. AI-Powered Platform Innovation: Exploring and implementing new AI capabilities that improve platform intelligence and operational efficiency. This is an exciting opportunity for someone who enjoys solving challenging technical problems using data, machine learning, and AI. In this role, you will collaborate closely with scientists, engineers, and product teams to develop and deploy production-ready solutions. You will conduct experiments, analyze large-scale data sets, build and evaluate machine learning models, and translate insights into impactful improvements for Microsoft AI products. As a Data and Applied Scientist II, you will apply statistical, machine learning, and deep learning techniques to analyze and interpret multimodal content, develop features and models that improve system capabilities, and help scale AI solutions to large-volume production environments. You will contribute to advancing state-of-the-art approaches while delivering measurable impact to products used by millions of customers.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
OR equivalent experience.

Nice To Haves

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
Solid machine learning / computer vision / natural language processing experience and results in academy or industry. Publications in major ML/IR/NLP/CV conferences. Examples: ICML, NIPS, SIGIR, ACL, EMNLP, CVPR, KDD.
Experience in open source (spark, hbase, hadoop etc) or microsoft internal tech (cosmos, autopilot, azure) are big plus as well as most of our project/scenario is across system and AI areas.
Good communication skills and ability to work in collaborative environment.
Good design and problem-solving skills and an ability to innovate and solve challenging technical problems.
Passion and self-motivation.
Embrace engineering excellence and delivering quality results at scale.

Responsibilities

Develop expertise in relevant machine learning, deep learning, and multimodal AI techniques, and apply them to solve challenging problems in image indexing, content understanding, selection, and ranking.
Partner with scientists, engineers, and product managers to understand business and product requirements, translate them into data-driven solutions, and deliver measurable product impact.
Design, implement, and evaluate machine learning and deep learning models, including Large Language Models (LLMs), Small Language Models (SLMs), and multimodal models for document understanding, content discovery, parsing, clustering, selection, and ranking.
Conduct large-scale data analysis and experimentation to identify opportunities for improving image index quality, freshness, relevance, and diversity.
Develop robust evaluation methodologies and analyze experiment results to drive model improvements and support data-informed decision making.
Contribute to near real-time indexing systems and AI-powered platform capabilities that improve multimedia content discovery and user experiences.
Work with petabyte-scale datasets and Big Data technologies to build, validate, and optimize machine learning solutions for production environments.
Document experiments, model performance, methodologies, and key learnings, and communicate findings effectively with teammates and stakeholders.
Follow responsible AI, privacy, security, and data governance best practices throughout the model development lifecycle.
Collaborate across Microsoft with engineers, scientists, and product teams to develop, deploy, and operate scalable AI solutions that serve billions of multimedia documents.
Stay current with advancements in machine learning, deep learning, generative AI, and multimodal systems, and apply relevant innovations to improve product capabilities.
Contribute to the delivery of state-of-the-art models and data-driven features that enhance the Microsoft AI Multimedia Index platform.