|Job Type:||Full Time|
Microsoft’s vision for Azure Machine Learning http://azure.com/ml is to make machine learning technology accessible to every enterprise, data scientist, developer, information worker, consumer, and device, anywhere in the world. Traditional data analysis tools are no longer sufficient to draw rich insights from terabytes and petabytes of data.
We are building the Azure Machine Learning service that will make it easy for all data scientists and AI developers to create and deploy robust, scalable and highly available machine learning solutions in the cloud. We are using the best of the open source ecosystem and
innovation from inside the company and the latest breakthroughs in research and bringing them to everyone, not just companies specializing in AI and ML.
We are looking for software engineers who are passionate about designing and building a machine learning platform for on-premises, cloud and hybrid environments. You will have an opportunity to design and scale advanced machine learning and statistical techniques to work on petabyte-scale datasets using a highly available distributed infrastructure. The successful candidate will bring a live-site oriented mindset, an iterative approach to services development, and an understanding of “big data” problems and solutions.
This position is for an engineer focused on developing high-performance computing solutions for machine learning workloads using modern frameworks like Kubernetes. As a software engineer in our organization, you will be responsible for creating the compute infrastructure that allows data scientists and developers to build, train, and validate their machine learning models at enterprise scale. The computing solutions you develop will allow our customers to run model training jobs across 100s of GPUs with lightning-fast communication through Infiniband and distributed file systems. You will both develop the code and work directly with live customers to ensure their jobs run fast and finish correctly -- every time.
We value passion, creativity, and desire to learn new complex technical areas, agility and accountability while pivoting a team towards greater results. You will be responsible for fully understanding requirements and providing solutions that match the needs.
- 5+ years software design and development skills/experience
- Knowledge and or experience of at least one of Python, C#, Java, C++, Go, or Rust – the key languages used in high-performance computing and data science
- Bachelor’s degree or higher in computer science or related areas
- Professional experience with Kubernetes and Docker technologies
- Design and deployment of new back end services, distributed systems, public APIs
- Passionate about machine learning and data science at high scale
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.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.