Machine Learn Eng 5

Job Description

Key Responsibilities

• Define and champion the 3–5+ year technical vision for edge inference — model architectures, optimization paradigms, compiler/ML hardware co-design, and ecosystem strategy primarily for Lattice sensAI, with extensions to other platforms (e.g., NXP NPUs, Arm-based systems)
• Lead high-impact, ambiguous initiatives spanning hardware, compiler, software, and product teams.
• Architect and drive adoption of groundbreaking techniques: hardware-aware NAS, quantization, dynamic/sparse inference, automated co-design flows for multi-platform deployment
• Serve as technical expert, aligning ML strategy with company business goals, hardware roadmaps (Lattice and partners), and long-term competitive positioning. Mentor staff and senior ML engineers, fostering a culture of technical excellence and innovation in cross-platform edge AI.
• Identify and resolve the most complex, organization-spanning bottlenecks in edge inference performance/power/accuracy across Lattice FPGAs and other accelerators.
• Own strategic evolution of the sensAI Model Zoo as a flagship industry resource (ecosystem partnerships, standardization, open benchmarks with support for NXP and similar platforms).
• Guide creation of advanced R&D prototypes, datasets, and frameworks that shape future sensAI generations and partner integrations.

Required Skills and Qualifications

• 10+ years of progressively responsible experience in edge AI, with demonstrated company-wide impact in efficient neural networks across diverse hardware
• World-class mastery of DL frameworks, model optimization, and edge deployment ecosystems (including cross-platform tools like ONNX Runtime)
• Pioneering expertise in extreme efficiency techniques and hardware/ML co-design for FPGAs and NPUs
• Track record of full-stack leadership on complex edge AI systems (Lattice FPGAs, NXP NPUs/custom accelerators)
• Exceptional ability to influence senior stakeholders, define strategy, and drive ambiguous initiatives
• PhD in CS, EE, AI/ML or equivalent strongly preferred (with significant research/industry contributions)

Additional Information