As the Director of Software AI/ML, you will lead a multidisciplinary group responsible for building the complete SDK and software enablement stack for our AI server platform. This includes a compiler and toolchain team, a machine learning applications team, and a DSP kernel optimization team. The ideal candidate will bring a blend of deep software expertise, system-level hardware understanding, and experience with AI/ML workloads and compiler design.

This is a key strategic role that bridges product, platform, and technology — ensuring that developers and customers can easily and efficiently utilize our platform to the fullest.

Key Responsibilities:

Leadership & Strategy:

• Define and execute the roadmap for the software tools group aligned with product and hardware architecture goals.
• Lead, mentor, and scale three sub-teams:
• SDK/Compiler Team: Responsible for building compilers, IR transformations, codegen, and debugging/profiling tools targeting the custom hardware platform.
• ML Applications Team: Develops and validates real-world AI workloads and models on reference and production hardware.
• DSP Kernel Team: Focused on writing and optimizing compute kernels (e.g., GEMM, convolutions, transforms) for the company’s platform.

Technical Oversight:

• Guide architecture and design decisions across compilation toolchains, AI frameworks integration, kernel optimization, and simulation/emulation infrastructure.
• Collaborate with hardware architects to co-design hardware features and SW enablement interfaces.
• Work with system and platform engineering to define APIs, runtime behavior, and debugging hooks.

Cross-Functional Execution:

• Act as the key interface to product management, hardware, firmware, and customer engineering teams.
• Ensure SDKs and tools are robust, performant, and easy to use for customers and internal teams.
• Drive test, simulation, and validation methodologies for early hardware bring-up and software stack readiness.

Requirements:

• 10+ years in software engineering, with 5+ years in technical leadership or management roles.
• Proven experience in managing compiler, toolchain, or system software development teams.
• Deep understanding of AI/ML workloads and frameworks (e.g., PyTorch, TensorFlow, ONNX).
• Strong knowledge of hardware/software co-design principles, especially in the context of AI accelerators, GPUs, or embedded platforms.
• Background in kernel development or DSP/low-level optimization techniques (SIMD, vectorization, memory locality).
• Experience in building developer-facing SDKs or performance tooling for new platforms.
• Solid grasp of C++, Python, LLVM/MLIR or similar compiler frameworks.

Preferred Qualifications:

• Experience working in a startup or high-growth hardware company.
• Contributions to open-source AI or compiler ecosystems.
• Experience with end-to-end performance benchmarking and tuning for ML workloads.