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The MTIA (Meta Training & Inference Accelerator) Software team is part of AI and Compute Foundation organization. The team’s mission is to explore, develop and help productize high-performance software and hardware technologies for AI at datacenter scale. The team co-optimizes both SW (e.g., algorithms and models) and HW (e.g., platform and network) to come up with balanced system design. To develop new systems, requires understanding performance bottlenecks on existing systems. As a result, the team invests significantly into optimizing AI production models on existing systems. This has resulted in TCO wins for all key AI services. Team has been developing AI compilers to accelerate Meta’s DL/ML workloads on the specialized MTIA AI accelerator hardware in a highly performant and flexible way. As part of the AI acceleration software stack, we develop compiler optimizations exploiting various hardware architectural features, achieving high performance for our inference and training workloads.
Job Responsibility:
Grow a team of domain experts in neural network end-to-end performance optimization, compiler tool chain development, hardware/software co-design technologies
Manage wide-ranging teams of researchers and developers, help them develop their careers, assigning them to projects tailored to their skill levels, long-term skill development, personalities, and work styles
Communicate and collaborate effectively with cross-functional hardware and software engineering teams
Champion engineering and operational, establishing metrics and process for regular assessment and improvement
Operate strategically and tactically. Develop the team's vision and strategy to help set direction, while staying on top of the day-to-day software development
Work closely with dedicated recruiting staff to expand the team, including sourcing candidates, interviewing candidates, participating in conferences/events, and on-boarding new employees
Requirements:
At least 5 years of experience in managing a software team in a fast-paced capacity
Demonstrated experience in managing other managers
Proven understanding and experience executing full product life-cycles (prototyping, deployment, and support)
Nice to have:
Accelerator (GPU/ASIC) compiler development and neural network optimization
Experience in compiler infrastructures, IR frameworks and toolchains such as Inductor, MLIR, or LLVM
Experience with different programming models for high-performance computations, e.g. CUDA, Triton or OpenCL
Experience working closely with hardware architectures such as Intel SIMD, GPU, RISC-V, AI accelerators, etc
Experience in hardware-software development environments such as simulators, FPGA emulators etc
Knowledge of ML frameworks like PyTorch, TensorFlow, ONNX, MXNet, etc