Staff Software Engineer
1 month ago
You will help to build the software that enables development of deep learning applications that form the basis of many ground-breaking technologies like self-driving cars, generative AI engines and ML-powered wearables.
Job Overview:
Arm Machine Learning (ML) Compilers team is looking for an experienced software engineer who would build a range of innovative compiler solutions for a variety of markets.
You will apply your experience and insight within this domain to craft and optimise compilers for machine learning networks that target Arm's CPUs, GPUs and NPUs.
If you are interested in this opportunity, make sure to apply soon We look forward to receiving your application and welcoming you to Arm.
Responsibilities:
Build, extend and collaborate on innovative ML compilation software projects, such as TensorFlow, IREE and the broader MLIR ecosystem
Contribute to deliver production-grade software and push the boundaries of Machine Learning compilation
Work with other groups in Arm to expand support for Arm architecture and ecosystem
Required skills and experience:
Solid understanding in at least one programming language such as C++, Python, Java, etc.
Experience with the full software development lifecycle - planning, designing, developing, testing, delivering, and maintaining production-quality software
Experience with contributing to open-source projects and working with a broader open-source community
Experience with or interest in compilers
Desire to learn new skills and technologies and work in a highly motivated team
High degree of initiative and problem solving skills
Ability to own team's delivery and lead others on large or more sophisticated tasks
"Nice to have" skills and experience:
Technical leadership experience
Knowledge or curiosity about computer vision, machine learning, their applications and frameworks
Experience with Linux and scripting languages, such as shell-scripting
In Return:
On top of the already compelling , we offer strong team culture, learning opportunities, regular career conversations, emphasis on diversity, equity and inclusion and a continuous improvement mentality.
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