Azure AI Search provides a secure, at scale, search engine over user-owned data. The data and applied science team develops the machine learning components that power the search engine, both for traditional and generative AI scenarios such as RAG (retrieval-augmented generation). Our goal is to deliver high quality search results for very different industries, corpus sizes and scenarios, and our work includes multiple aspects, among which:
Training and fine-tuning of deep learning models, including language models, often with tight latency constraints; Collection, generation and filtering of training and evaluation data; Metrics development; Keeping up with research and industry trends. As a team, we leverage the diverse backgrounds and experiences of passionate engineers, scientists, and program managers to help us realize our mission to empower every person and every organization on the planet to achieve more. We believe great products are built by inclusive teams of customer-obsessed individuals who trust each other and work closely together. We collaborate regularly across the company with teams like Bing and Microsoft Research.
If you are passionate about working on the latest and hottest areas in Artificial Intelligence, Machine Learning and data science, all the while making search better for customers across the world and being part of one of the biggest cloud providers, then this is the team you're looking for!
Responsibilities As part of the team, you will be responsible for different aspects, such as:
Train, fine-tune, domain adapt and distill large scale NLP models for real-world large-scale applications; Work on the full lifecycle of machine learning development, including training data collection, model training, component and end-to-end evaluation; Design and get high quality labels for a wide range of techniques (retrieval, ranking, machine reading comprehension etc.); Select, develop and build metrics to use across the full range of search engine components; Incorporate customer feedback into evaluations and models development; Contribute to experimentation infrastructure and proofs-of-concept to test out new ideas and concepts; Understand existing code and write new code that is efficient and readable; Partner effectively with program management, engineers, and other functions across products; Document work and communicate in a clear and efficient way. Qualifications Required Qualifications: Bachelors, Masters or advanced degree in Computer Science or related field (including Mathematics and Physics). Relevant industry experience in applying Machine Learning techniques. Relevant experience in coding in Python, C#, Java or C++. Preferred Qualifications: MS or PhD in computer science or related field. Experience with machine learning frameworks such as PyTorch, ONNX, etc. Experience with deep model training and evaluation. Experience with using large language models. Customer focused, strategic, drives for results, is self-motivated, and has a propensity for action. Problem solver: ability to solve problems that the world has not solved before. Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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