AI Architect – Media

Jobtailor; Atlanta (GA); On-site; USD 180,000 - 240,000; Full time

Job summary

Dolby is seeking a senior AI/ML leader in Atlanta to define and guide technology strategy across audio and video processing, personalization, and related domains, spanning cloud, edge, and embedded environments. You will translate research into production-ready recommendations and influence cross-functional teams to deliver optimized ML solutions.

The role requires deep experience with ML frameworks, model optimization, and hardware accelerators, with familiarity in Dolby technologies such as

Qualifications

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or related field, or equivalent practical experience.
• Significant hands-on experience in AI, machine learning, and embedded software engineering.
• Strong software engineering skills, including production-quality code and pipelines.
• Experience with at least one major AI/ML framework (PyTorch, TensorFlow, JAX, ONNX).
• Experience deploying optimized ML models using quantization, pruning, distillation, or operator fusion.
• Experience with edge or on-device ML and latency/power/memory constraints.
• Familiarity with CPU/GPU/NPU/DSP architectures and toolchains (Hexagon/QNN, APU/NeuroPilot, Ethos, ANE).
• Experience in audio, video, signal processing, codecs, or related domains.
• Ability to work across model to hardware performance abstractions.
• Experience shipping ML models to production on resource-constrained devices.

Responsibilities

• Define and guide AI/ML technology strategy across Dolby’s core technology areas.
• Develop strategy spanning cloud, edge, and embedded environments with emphasis on edge ML.
• Establish best practices, guardrails, and guidelines for ML model lifecycle.
• Translate AI/ML trends into production-oriented recommendations for hardware.
• Serve as primary technical interface between ML research and engineering teams.
• Define architectures integrating audio/video processing, DSPs, accelerators, and ML models.
• Partner with platform managers to integrate ML models into products.
• Collaborate with researchers to align requirements and constraints.
• Help establish data governance standards with Data Engineering.
• Collaborate with QA on AI/ML testing methodologies.

Skills

AI/ML Frameworks (PyTorch, TensorFlow,

Edge Machine Learning Deployment

GPU/NPU/DSP Architecture Familiarity

Technical Strategy Definition

Real-Time Audio/Video Inference Pipeli

Education

Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or related field

Tools

Qualcomm Hexagon/QNN

MediaTek APU/NeuroPilot

Version Control Systems

Build Systems

Software Delivery Pipelines

Job description

• Define and guide AI/ML technology strategy across Dolby’s core technology areas, including audio processing, video processing, personalization, and related domains
• Develop strategy spanning cloud, edge, and embedded environments, with emphasis on edge ML, GPUs, and NPUs
• Anticipate business and technical needs and contribute to long-term technical vision
• Establish best practices, guardrails, and guidelines for building, training, optimizing, and deploying ML models
• Translate AI/ML industry trends and emerging architectures into production-oriented recommendations for accelerated hardware
• Serve as the primary technical interface between ML research and engineering teams
• Define architectures integrating traditional audio/video processing, DSPs, hardware accelerators, and ML models
• Partner with platform managers and engineering teams to integrate ML models into shipped products
• Collaborate with researchers to align requirements and constraints
• Help establish data governance standards for sourcing, cleaning, and pipeline management with Data Engineering
• Collaborate with QA teams on AI/ML testing methodologies
• Evaluate GPU and NPU architectures, toolchains, operator support, and performance
• Identify gaps between model requirements and hardware capabilities and drive solutions with internal teams and external partners
• Influence silicon vendors and platform partners on roadmaps, tooling, and hardware capabilities
• Conduct technical investigations and experiments, including model profiling, inference benchmarking, and accuracy/latency trade-off evaluation
• Apply and advise on retraining, pruning, quantization, distillation, and hardware-aware optimization
• Guide model porting across frameworks and runtimes such as PyTorch, ONNX, and vendor-specific runtimes
• Build prototypes and proofs of concept to reduce technical risk before engineering investment
• Translate advanced ML research into efficient, scalable, production-ready solutions across Dolby’s product portfolio

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
• Strong software engineering skills, including production-quality code, 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
• Hands-on experience deploying optimized ML models using quantization, pruning, distillation, or operator fusion
• Experience with edge or on-device ML and constraints involving latency, power, memory, and thermal limits
• Familiarity with CPU, GPU, NPU, and DSP architectures and associated toolchains, including 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
• Ability to work across abstraction layers from model architecture to operator-level hardware performance
• Experience defining technical strategy and influencing cross-functional teams
• Experience shipping ML models to production on resource-constrained devices
• Experience with real-time audio/video inference pipelines
• Familiarity with Dolby technologies such as Atmos, Vision, or AC-4, or comparable media standards
• Experience with generative AI models in audio or video
• Contributions to open-source ML tools or peer-reviewed research

Core Competencies

Demonstrates expertise in AI/ML technology strategy, focusing on edge ML, GPUs, and NPUs, while integrating audio and video processing with machine learning models. Proven ability to influence cross-functional teams and establish best practices for deploying optimized ML solutions in production environments.

Highest-signal resume keywords

• AI/ML Frameworks (PyTorch, TensorFlow, JAX, ONNX)
• Edge Machine Learning Deployment
• GPU/NPU/DSP Architecture Familiarity
• Technical Strategy Definition
• Real-Time Audio/Video Inference Pipelines

Hard Skills

• Machine Learning
• Embedded Software Engineering
• Production-Quality Code
• Model Optimization Techniques (Quantization, Pruning, Distillation)
• Audio/Video Signal Processing

Soft Skills

• Collaboration
• Influencing Cross-Functional Teams
• Technical Communication

Industry Keywords

• Data Governance Standards
• Generative AI Models
• Dolby Technologies (Atmos, Vision, AC-4)
• Media Codecs
• Open-Source ML Contributions

Tools & Technologies

• Version Control Systems
• Build Systems
• Software Delivery Pipelines
• Qualcomm Hexagon/QNN
• MediaTek APU/NeuroPilot