AI20P Library Engineer, Machine Learning Acceleration

About the Role

We are seeking a highly skilled AI20P Library Engineer to bridge the gap between cutting-edge AI research and our hardware accelerators. In this role, you will design, develop, and optimize high-performance software libraries, kernels, and parallel compute runtimes for distributed AI20P environments.

You will empower ML researchers and cloud developers to train and deploy frontier AI models at unprecedented scales.

Key Responsibilities

• Design, implement, and tune high-performance custom operators and mathematical kernels specifically for AI20P architectures (assembly or intrinsic level).
• Build software abstractions and libraries that manage multi-host setups, sharding, and multi-dimensional parallelization (e.g., Megatron-LM style tensor/pipeline parallelism).
• Design and optimize custom collective communication algorithms (AllReduce, AllGather) to minimize latency and maximize throughput over high-speed interconnects.
• Profile distributed training workloads to identify and eliminate memory bottlenecks, network stalls, and suboptimal hardware utilization.
• Partner with compiler developers (XLA), hardware architects, and research scientists to co-design the future software-hardware ecosystem.
• Develop and maintain high-quality, well-documented code that adheres to industry standards and best practices.

Skills & Qualifications

• B.S., M.S., or Ph.D. in Computer Science, Electrical Engineering, or a highly quantitative field.
• Exceptional proficiency in C++ and Python.
• Hands-on experience with at least one major AI/ML framework (e.g., JAX, PyTorch).
• Strong understanding of concurrent computations, memory hierarchies (HBM, cache), and hardware accelerators.
• Excellent cross-functional communication skills to translate complex research needs into production-ready software architecture.
• Experience working with compiler construction or optimizing code generation for hardware.
• Familiarity with cloud-based cluster managers (e.g., Kubernetes, SLURM) for executing large-scale distributed ML workloads.

What You'll Learn

In this role, you will gain hands-on experience with cutting-edge AI research and hardware accelerators, as well as develop expertise in designing and optimizing high-performance software libraries and kernels.

You will also have the opportunity to collaborate with a talented team of researchers and engineers to co-design the future software-hardware ecosystem.

Resume Tip

When applying for this role, be sure to highlight your experience with AI/ML frameworks, concurrent computations, and hardware accelerators. Additionally, include any relevant projects or contributions you have made to optimizing Large Language Models (LLMs) or multimodal architectures.

Use specific examples to demonstrate your skills and experience, and be prepared to discuss your qualifications in detail during the interview process.