About the job
Are you passionate about building best multimedia search experience on the web and helping billions of internet users find the most relevant and enjoyable image/video content on the web? Unique challenge of multimedia search depends on talents from diversified technical backgrounds. Do you want to work with a group of talented data and applied scientists and distributed system engineers to grow your experience/career in wide range of areas including computer vision, natural language processing, machine learning, deep learning, big data mining, and information retrieval etc.? If so, this applied scientist/ML engineer position on Bing multimedia relevance team will be a great fit for you!
Responsibilities
Analyze problems through all data available to you including large scale crawled data and user engagement data etc.
Define problems and metrics to address various problems including relevance, authority, attractiveness, diversity, and freshness etc.
Design and train ML system and model architecture.
Collect data for training. Define engineer life cycle and drive project forwards through iterative ranker releases.
Understanding search stack and platform in order to deploy models to production.
Collaborate with other data & applied scientists as well as distributed system engineer and program manager.
Proactively seeks mentorship from others.
Qualifications
Minimum
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ 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 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
Preferred
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years 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.