AI Architect - Media
About The Position
Dolby is seeking a Senior Staff AI / Machine Learning Architect to bridge research teams and product engineering organizations, translating advanced machine learning research into efficient, scalable, production-ready solutions across Dolby’s product portfolio. The role helps define technical strategy for developing, training, optimizing, and deploying AI/ML models, particularly for edge ML and NPU-enabled platforms. It combines hands-on engineering with system-level thinking and technical leadership across projects and teams. The architect will guide AI/ML strategy across audio processing, video processing, personalization, and related domains spanning cloud, edge, and embedded environments. The role works closely with researchers, software engineers, data and QA teams, platform managers, silicon vendors, and platform partners to align requirements, hardware capabilities, and product constraints. It includes technical investigations, model profiling and benchmarking, optimization, framework and runtime porting, and prototyping to reduce risk before full engineering investment. This is a production-focused technical leadership role, not a pure research, people-management, MLOps, LLM-only, infrastructure-focused, or third-party API integration role. The work involves developing proprietary models and translating research into production-ready solutions.
Requirements
- 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, typically acquired over many years of professional practice.
- Strong software engineering skills, including production-quality coding and experience with version control, testing, build systems, and software delivery pipelines.
- Experience with at least one major AI/ML framework, such as PyTorch, TensorFlow, JAX, or ONNX, and ability to learn additional frameworks as needed.
- Hands-on experience deploying optimized ML models, including techniques such as quantization, pruning, distillation, or operator fusion.
- Experience with edge or on-device ML and awareness of constraints such as latency, power, memory, and thermal limits.
- Familiarity with CPU, GPU, NPU, and DSP architectures and associated toolchains, such as Qualcomm Hexagon/QNN, MediaTek APU/NeuroPilot, ARM Ethos, or Apple Neural Engine.
- Experience in audio, video, signal processing, media codecs, or closely related technical domains.
Nice To Haves
- Ability to work across abstraction layers, from model architecture to operator-level hardware performance.
- Experience defining technical strategy and influencing cross-functional teams through expertise and collaboration.
- Demonstrated experience shipping ML models to production on resource-constrained devices, such as mobile, embedded, automotive, or wearable devices.
- Experience with real-time audio/video inference pipelines, such as streaming inference, causal models, or latency-sensitive processing.
- Familiarity with Dolby technologies such as Atmos, Vision, or AC-4, or comparable media standards.
- Experience with generative AI models in the audio or video domain.
- Contributions to open-source ML tools or peer-reviewed research.
Responsibilities
- Define and guide AI/ML technology strategy across Dolby’s core technology areas, including audio processing, video processing, and personalization, across 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.
- Track developments in AI/ML and translate emerging architectures and edge inference techniques into practical 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, and 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 requirements and constraints.
- Work with Data Engineering teams to 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.
- Develop a working understanding of GPU and NPU architectures, toolchains, operator support, and performance characteristics.
- Identify gaps between model requirements and hardware capabilities, and help drive solutions with internal teams and external partners.
- Collaborate with and influence silicon vendors and platform partners on roadmap alignment, tooling, and hardware capabilities relevant to Dolby use cases.
- Conduct technical investigations and experiments, including model profiling, inference benchmarking, and evaluation of accuracy-latency trade-offs.
- Apply and advise on model optimization techniques such as retraining, pruning, quantization, distillation, and hardware-aware optimization.
- Guide model porting across frameworks and runtimes, such as PyTorch to ONNX to vendor-specific runtimes.
- Build prototypes and proof of concepts to reduce technical risk before full engineering investment.
Benefits
- Excellent compensation and benefits.
- Bonus; some roles may also include equity.
- Flexible work approach supporting where, when, and how employees work.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
