PhD Research Intern - Data Management & Visualization; Fall , Atlanta

Join the leader in entertainment innovation and help us design the future. The Advanced Technology Group (ATG) is the research division of the company. ATG’s mission is to look ahead, deliver insights, and innovate technological solutions that will fuel Dolby’s continued growth. As a valued member of the Dolby team, you’ll see and hear the results of your work everywhere, from movie theaters to smartphones.

We continuously push the boundaries of audio, imaging, and cloud technology to create spectacular entertainment experiences.

As a diverse and dynamic group, our ATG researchers work on cutting‑edge projects related to computer science and electrical engineering for audio, video, and cloud technologies, exploring exciting domains such as AI/ML, algorithms, digital signal processing, audio processing, image processing, computer vision, AR/VR, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.

The Data Platform & AI Services research team within Dolby's Advanced Technology Group focuses on advancing our AI and data platforms to enable AI‑based innovation and deliver cloud and network‑delivered media experiences to power the world’s most influential media service providers.

We are looking for a PhD Research Intern in ML Data Platform & Visualization to extend our existing data platform with scalable tooling that helps ML researchers understand, navigate and extract insight from large‑scale multimodal datasets. You will build on a production‑grade platform while drawing on and contributing to emerging research in visualization for machine learning, data‑centric AI, and foundation model interpretability.

• Extend our ML data platform to improve dataset management, discoverability, and quality assessment for large‑scale, multimodal media datasets (video, image, audio, sensor data).
• Build scalable visualization tooling that enables ML researchers to explore embedding spaces, surface semantic representations from foundation models, and understand dataset structure at scale.
• Design and implement interactive data exploration interfaces to support ML research workflows and data management, including ingestion, indexing, retrieval, annotation and representation.
• Investigate and apply emerging research in visualization for ML, data‑centric AI, and foundation model representations to inform platform design decisions.
• Collaborate directly with AI researchers to translate research workflows into platform requirements, bridging the gap between model development needs and data infrastructure capabilities.
• Present your work to internal stakeholders, with the possibility of contributing to academic publications or conference presentations.

• Currently enrolled in a PhD program in Computer Science, Human‑Computer Interaction, Computational Media, Data Science, Electrical Engineering, or a related field, with interest in data management, data visualization, ML infrastructure, or media data systems.
• Strong background in data management and visualization, including data modeling, indexing, retrieval, annotation and visualization for large‑scale or unstructured media data.
• Familiarity with ML workflows and researcher tooling — understanding how ML researchers interact with datasets during training, evaluation and debugging.
• Solid understanding of deep learning fundamentals and experience with frameworks such as PyTorch.
• Proficiency in Python and experience with visualization libraries.
• Ability to work independently and as part of a collaborative, cross‑disciplinary research team.

• First‑authored publication or project work in relevant domains at top venues such as IEEE VIS, CHI, VLDB, ACM SIGMOD, SIGKDD or IEEE Big Data.
• Expertise in visualization research for ML, including dataset cartography, latent space visualization, data‑centric AI, or interactive ML tools.
• Hands‑on experience building data visualization tools or interactive ML exploration interfaces — embedding viewers, dataset dashboards, annotation UIs, or similar.
• Experience with scalable data processing and model training.

• Currently enrolled…