Join Annapurna Labs, a cutting-edge subsidiary of Amazon Web Services (AWS), where we're pioneering hardware/software co-design across the industry. As a Software Engineer II in our Machine Learning Server Software Team, you'll be at the forefront of developing sophisticated software solutions for our advanced ML servers.
Our team specializes in the physical systems that power machine learning acceleration, focusing on critical components from accelerator operations to I2C infrastructure. We're not working on ML algorithms directly, but rather building and maintaining the hardware systems that make ML execution possible and efficient.
Your role will involve creating and maintaining software packages that enable both qualification and rapid deployment of our systems. You'll work extensively with C/C++, Python, and Lua, developing maintainable and reusable code that meets our high standards for documentation and testing. Collaboration is key as you'll work closely with MLA Hardware, Test, and Manufacturing teams to create integrated software solutions.
We pride ourselves on our inclusive team culture and commitment to professional growth. Our environment celebrates knowledge-sharing and mentorship, with senior team members providing one-on-one guidance and constructive code reviews. We're dedicated to helping you develop your engineering expertise and take on increasingly complex challenges.
AWS, as the world's leading cloud platform, offers unparalleled opportunities to work on innovative technologies that power businesses worldwide. We value diverse experiences and perspectives, fostering an inclusive environment through employee-led affinity groups and ongoing learning experiences. Our commitment to work-life harmony ensures you can maintain a healthy balance between professional achievement and personal well-being.
Join us to be part of a team that's shaping the future of machine learning infrastructure while growing your career with one of technology's most innovative companies. Whether you're interested in system architecture, performance optimization, or hardware integration, you'll find challenging and rewarding opportunities to make your mark in cloud computing.