AI Architect

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

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 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

Conduct 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

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

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 (e.g., mobile, embedded, automotive, wearables)

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

This 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 $152,000 - $209,000, 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 Opportunity: Dolby 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.