AI Architect

In this role, you will help translate advanced machine learning research into efficient, scalable, and production ready solutions across Dolby’s product portfolio. * Define and guide AI/ML technology strategy across Dolby’s core technology areas (audio processing, video processing, personalization, and related domains), spanning cloud, edge, and embedded environments, with a focus on edge ML, GPUs, and NPUs * Anticipate evolving business and technical needs and contribute to a forward looking technical vision * Establish best practices, guardrails, and technical guidelines for building, training, optimizing, and deploying ML models across the organization * Stay current with developments in AI/ML, including emerging architectures and edge inference techniques, and translate industry trends into practical, production oriented recommendations for accelerated hardware * Serve as a primary technical interface between ML research teams and engineering teams * Define architectural approaches for integrating traditional audio/video processing (DSPs, hardware accelerators) with ML models * Partner with platform managers and engineering teams to integrate ML models into shipped products, and collaborate with researchers to align on requirements and constraints * Work with Data Engineering teams to help establish data governance guidelines and standards for data sourcing, cleaning, and pipeline management * Collaborate with QA teams to develop testing methodologies appropriate for AI/ML systems * Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or a related field, or equivalent practical experience * Significant hands on experience in AI, machine learning, and embedded software engineering (often acquired over many years of professional practice) * Strong software engineering skills, including experience writing production quality code and working with version control, testing, build systems, and software delivery pipelines * Experience with at least one major AI/ML framework (e.g., PyTorch, TensorFlow, JAX, ONNX) and the ability to learn additional frameworks as needed * Hands on experience deploying optimized ML models (e.g., quantization, pruning, distillation, operator fusion) * Experience with edge or on device ML, including awareness of constraints such as latency, power, memory, and thermal limits * Familiarity with CPU, GPU, NPU, and DSP architectures and their associated toolchains (e.g., Qualcomm Hexagon/QNN, MediaTek APU/NeuroPilot, ARM Ethos, Apple Neural Engine) * Experience in audio, video, signal processing, media codecs, or closely related technical domains Our salary ranges are determined by role, level, and location.

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