This position is part of a project for a world-renowned high-tech company focused on the foundational infrastructure behind large scale AI workloads. The team works with core ML compiler and runtime systems that enable AI execution on CPUs, GPUs, and specialized accelerators such as TPUs. The project centers on adapting, stabilizing, and validating complex, performance critical systems so they can operate reliably across different environments and release contexts, while remaining aligned with the evolution of modern AI frameworks.
Essential functions:
- Work with large existing C++ codebases related to ML compilation and runtime infrastructure.
- Adapt and evolve existing systems to operate correctly across multiple environments and deployment contexts.
- Improve portability, reliability, and consistency of core infrastructure components.
- Collaborate with compiler, framework, and infrastructure teams to ensure correct integration and validation.
- Contribute to the ongoing stabilization and refinement of AI infrastructure used at scale.
Qualifications:
- Strong proficiency in C++ with experience working in large, mature codebases.
- Familiarity with LLVM or compiler based systems.
- Understanding of CPU architecture and performance considerations.
- Familiarity with open source ML compiler or runtime projects targeting CPU or GPU.
- Experience working in Linux based development environments.
- Hands on experience working in containerized development or CI environments (Docker or similar).
- Working knowledge of Python for general engineering tasks and tooling.
- Bachelor Degree in Computer Science or similar.
Would be a plus:
- Exposure to large scale ML frameworks such as TensorFlow or JAX and their compilation or execution paths.
