Software Engineer/Senior Software Engineer Networking For AI

Job Overview:

We are seeking accomplished Software Engineers with a deep knowledge of developing and testing high performance networking software that is leveraged by AI frameworks. The successful candidates will have the opportunity to work with cutting-edge technologyoften before public releaseon development platforms, software models, FPGAs, and early silicon.

About Arm:

Arm is the industry leader in microprocessor technology, powering a vast ecosystem with over 1,000 partners and 90 billion processors shipped. Our innovations drive the computing and connectivity revolution across AI data centres, cloud infrastructure, and networking appliances.

Responsibilities:

As a Software Engineer in the IAS Networking team, you will:

• Design, develop, test and optimise high-performance networking software on Arm platforms, along with test cases and sample applications to ensure production-quality software,
• Work closely with internal and external partners to enhance networking stacks, and automate CI/CD pipelines,
• Contribute to open-source projects by developing, upstreaming, and maintaining code.
• Adapt quickly to different layers of the networking software stack.

Essential Skills & Experience:

In addition to having at least five years’ experience in either software development and optimization or software validation and test automation; the successful candidate should be:

• Highly proficient in C and C++,
• Have a strong grasp of multicore processor architectures and low-level systems,
• Experienced at developing tests, and improving software quality,
• Experienced with distributed version control systems (e.g. Git),
• A clear, effective communicator (both written and verbal).

“Nice To Have” Skills and Experience:

The following experience will be looked upon favorably:

• Familiarity with open-source software contribution processes,
• Highly proficient in Python,
• Hands on experience with network I/O drivers and L2-L7 networking stack consisting of data plane software such as DPDK, VPP, Snort, etc.
• Experience with networking software stack components for AI applications such as RoCE, libFabric, OpenMPI, NCCL, OneCCL, etc.
• Familiarity with PyTorch based training applications or concepts related to SDN and cloud native technologies such as Kubernetes and CNIs.