Are you excited about working on a new AI product that augments humans who need to reason with unstructured information? The AI empowerment org is well on its way to create this breakthrough product in long-term partnership with a handful of the largest enterprises globally. The product harvests, creates and harnesses a diverse range of AI models and automatically makes their output intelligible to humans on demand. Our product design point is to help people make sense of information buried in mountains of documents, conversations, photos, videos, 2D and 3D scans, molecular and genetic representations, and emerging device and sensor signals. If you are looking for an environment that actively blurs the distinction between engineers and applied scientists, and where involving the customer is just another day at work, then this is the team for you. **Responsibilities** **Who We Are:** As an important component behind this product, the MLSys team works on cutting edge ML system solution, covering the whole model development lifecycle, including but not limited to model management, deployment, registration, model performance optimization, training dataset preparation, etc. Our team of ML system engineers are constructing the next generation of machine learning platforms by marrying the latest ML industry practices with engineering excellence and the need to perform at Microsoft scale. Our customers are all the applied scientists and our goal is to provide a unified tooling ecosystem that allows these scientists to focus on what they are good at, building ML models with novel approaches, and abstract the way the complexities of bringing these models into a production environment. **Responsibilities:** Partners with stakeholders to design, develop, optimize, and productionize machine learning (ML) or ML-based solutions and systems that are used within a team to solve complex problems with multiple dependencies. This role also leads team efforts to leverage and improve ML infrastructure for model development, training, deployment needs and scaling ML systems. **Qualifications** **Required:** + 3+ years of handling services in a large scale distributed systems environment and experience in C#, Java, C++, or similar language + Engineering experience in hands-on software development with thoughtfulness of scale, latency and distributed architecture **Preferred:** + Experience working with machine learning inference/training framework, including but not limited to TensorRT, ONNX, Horovod, Ray, etc + Previous expertise on distributed systems and/or ML system + Comfortable working with on-prem and cloud-based infrastructure (Azure) in terms of deployment, support, monitoring, administration and troubleshooting + Strong empathy for the pain-points faced by other applied scientists, and the passion to solve them Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form (https://careers.microsoft.com/us/en/accommodationrequest) . Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Source : Microsoft Corporation