AI Architect - Media
dolbyMillbrae, CA
$176,000 per yearAPPLY NOW (opens in a new tab)
AI Architect - Media
dolbyMillbrae, CA
2 days ago
Occupations
Computer Systems Engineers/ArchitectsComputer and Information Research ScientistsDatabase ArchitectsIndustries
Computer Systems Design ServicesSoftware PublishersAll Other Professional, Scientific, and Technical Services$176,000 per year
APPLY NOW (opens in a new tab)About the role
Join the leader in entertainment innovation and help us design the future. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you’ll see and hear the results of your work everywhere, from movie theaters to smartphones. We continue to revolutionize how people create, deliver, and enjoy entertainment worldwide. To do that, we need the absolute best talent. We’re big enough to give you all the resources you need, and small enough so you can make a real difference and earn recognition for your work. We offer a collegial culture, challenging projects, and excellent compensation and benefits, not to mention a Flex Work approach that is truly flexible to support where, when, and how you do your best work.
Dolby’s consumer entertainment and cinema businesses are bringing Dolby’s breakthrough technologies, powering the world’s top movies, TV shows, music, games, and live sports to more places around the world across a wider range of consumer experiences and devices.
Role Overview:
We are seeking a Senior Staff AI / Machine Learning Architect to serve as a key technical bridge between research teams and product engineering organizations. In this role, you will help translate advanced machine learning research into efficient, scalable, and production ready solutions across Dolby’s product portfolio.
Key Responsibilities:
Technical Strategy and LeadershipDefine 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
Bridge Research and EngineeringServe 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
Engage with Silicon VendorsDevelop 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 in collaboration 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
Hands On Technical WorkConduct technical investigations and experiments, including profiling models, benchmarking inference, and evaluating 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 (e.g., PyTorch → ONNX → vendor specific runtimes)
Build prototypes and proof of concepts to reduce technical risk prior to full engineering investment
Qualifications:
RequiredBachelor’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
Strongly PreferredAbility 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 (e.g., mobile, embedded, automotive, wearables)
Nice to Have:
Experience with real time audio/video inference pipelines (e.g., streaming inference, causal models, 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
What This Role Is NotThis is not a pure research role; the focus is on translating research into production ready solutions
This is not an MLOps, LLM only, or infrastructure focused role
This role does not center on integrating third party APIs; the work involves developing proprietary models
This is not a people management role, though the position involves technical leadership and influence
The San Francisco/Bay Area base salary range for this full-time position is $176,000 - $215,000, which can vary if outside this location, plus bonus, benefits, and some roles may also include equity. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, competencies, experience, market demands, internal parity, and relevant education or training. Your recruiter can share more about the specific salary range and perks and benefits for your location during the hiring process.
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Dolby will consider qualified applicants with criminal histories in a manner consistent with the requirements of San Francisco Police Code, Article 49, and Administrative Code, Article 12
Equal Employment OpportunityDolby is proud to be an equal opportunity employer. Our success depends on the combined skills and talents of all our employees. We are committed to making employment decisions without regard to race, religious creed, color, age, sex, sexual orientation, gender identity, national origin, religion, marital status, family status, medical condition, disability, military service, pregnancy, childbirth and related medical conditions or any other classification protected by federal, state, and local laws and ordinances.
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JOB OVERVIEW
Salary
$176,000 per year
Experience level
Manager
Location
Millbrae, CA
Occupation
Computer Systems Engineers/Architects
Industry
Computer Systems Design Services
Posted
2 days ago
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