Software Engineer Systems Machine Learning - Frameworks

Responsibilities

• check_circle Development of software stack with one of the following core focus areas: AI frameworks, compiler stack, high performance kernel development and acceleration onto next generation of AI Accelerators architectures
• check_circle Contribute to the development of the PyTorch AI framework core compilers to support new state of the art inference and training AI hardware accelerators and optimize their performance
• check_circle Analyze neural networks, develop & implement compiler optimization algorithms
• check_circle Accelerate the next generation of deep learning models such as Recommendation systems, Generative AI, Computer vision, NLP etc
• check_circle Performance tuning and optimizations of deep learning framework & software components

Basic qualifications

• Python and C/C++ programming skills
• Experience in AI framework development or accelerating deep learning models on hardware architectures
• Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred qualifications

• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• OR AI Compiler: Experience with compiler optimizations such as loop optimizations, vectorization, parallelization, hardware specific optimizations such as SIMD. Experience with MLIR, LLVM, IREE, XLA, TVM, Halide is a plus
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience working with kernel frameworks like Triton, or CUDA
• OR AI frameworks: Experience in developing training and inference framework components. Experience in system performance optimizations such as runtime analysis of latency, memory bandwidth, I/O access, compute utilization analysis and associated tooling development
• Knowledge of GPU, CPU, or AI hardware accelerator architectures
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

About the company