Machine Learning Jobs in Cary, NC

Lead enterprise data engineering strategy and roadmap to build scalable cloud-native data platforms. Oversee design and modernization of data architectures, pipelines, and integration. Ensure data security, privacy, and governance, incorporate AI/ML, and drive data democratization. Lead global teams, collaborate with business and technology leaders, and deliver enterprise-wide data capabilities to enable analytics, innovation, and business growth.

Lead bench-scale heterogeneous catalyst discovery for renewable fuels: design and synthesize iron-based Fischer-Tropsch and non-noble hydrodeoxygenation catalysts; perform end-to-end characterization (XRD, BET, TPR/TPD, chemisorption, XPS, TGA, TEM); deliver ML-ready experimental data to the platform; support 100 g scale-up and bench-pilot demonstrations; maintain rigorous, safety-focused laboratory practices.

Lead R&D for next-generation image and video coding using ML/AI. Design and implement video algorithms, codecs, and multimedia workflows, represent Disney in standards bodies, drive architectural innovation, and produce IP while collaborating globally across media processing, encoding, and streaming domains.

Lead analytics and forecasting for the Fortnite ecosystem: maintain core reporting, build time series forecasts and department-wide data models, perform executive analyses, ensure data quality, support self-service pipelines, and collaborate with engineering and product to drive data-driven decisions.

Lead analytics to inform Finance and Product for the Fortnite ecosystem. Maintain core reporting and forecasting, build time-series models, develop shared data models, perform executive analyses, ensure data quality, support self-service pipelines, and collaborate cross-functionally to improve data-driven decision-making.

Lead MarTech strategy and hands-on execution for AI-driven, real-time 1:1 personalization. Evolve and evaluate MarTech stack, integrate AI/ML decisioning, build real-time journeys in Adobe Experience Platform, define XDM schemas and identity resolution, monitor dataflow health, lead Agile delivery pods, translate strategy to technical requirements, and create executive-level measurement and governance frameworks.

As an AI writer, you will evaluate AI-generated writing, review human writing, and produce original content, mainly in Korean, contributing to AI development.

Lead end-to-end semiconductor product lifecycle from concept to high-volume manufacturing. Define validation, qualification, reliability and ESD/latch-up strategies. Drive statistical characterization, yield analysis, failure analysis, and AI/ML-enabled analytics. Influence cross-functional decisions, mentor engineers, and ensure product readiness through data-driven qualification and reliability practices.

Design and evaluate memory architectures for foundation models across modalities. Build production-ready, scalable learning models, define memory metrics, collaborate with researchers, and recommend roadmap improvements for long-horizon behavior and efficient storage/retrieval.

Design and evaluate general memory architectures for foundation models across modalities. Develop production-ready, scalable learning models, define memory evaluation metrics, and collaborate with researchers to roadmap improvements.

Paid 6–12 month research internship on Epic's Special Projects & Research team. Build and evaluate ML models across vision, language, and audio to support player safety, game agents, world and content generation, and developer tools. Own data analysis and dataset creation, implement end-to-end models, run experiments, and collaborate with research scientists and engineers on deploying models at scale.

The role involves designing and optimizing recommendation systems for Fortnite's Discover experience, including model implementation and A/B testing.

Design and optimize recommendation systems using deep learning approaches, manage pipelines and evaluate A/B tests to improve user experiences.

Build and productionize ML models and data pipelines, implement MLOps and CI/CD, monitor and retrain models, define ML frameworks and best practices, mentor hires, and collaborate with product and data teams to drive ML roadmap and operational excellence.