Machine Learning Jobs in Cary, NC

Designs and delivers enterprise data and AI capabilities from concept through production. Responsibilities include defining target architectures, evaluating build-versus-buy decisions, building hands-on data and AI solutions, reviewing code and models, guiding platform adoption, and advising executive stakeholders. The role covers machine learning, generative AI, RAG, agent architectures, semantic layers, MLOps, model governance, cloud data platforms, and production readiness in a regulated environment.

Leads enterprise architecture strategy and multi-year roadmaps for US Group domains, embedding generative AI, agentic systems, automation, and Azure cloud capabilities. Oversees modernization, integration, architecture governance, standards, and secure scalable solutions across legacy and cloud environments. Advises executives, influences technology decisions, mentors architects and engineers, and ensures AI initiatives produce measurable business value in a regulated enterprise.

Develop and integrate computer vision and machine learning algorithms for autonomous agricultural and off-highway equipment. Responsibilities include geometric computer vision, SLAM, localization, mapping, triangulation, depth estimation, camera calibration, data collection and processing, model development, training, optimization, deployment, and monitoring. The role uses cameras, LiDAR, radar, edge devices, robotics, cloud technologies, C++, and Python while collaborating onsite with engineering teams.

Leads the strategic direction of independent medical education and scientific content solutions. Provides clinical oversight, develops evidence-based content strategies and therapeutic plans, ensures medical accuracy and defensibility, and partners with editorial, product, project, commercial, and scientific stakeholders. The role monitors clinical evidence and regulatory developments, advises on complex content decisions, engages key opinion leaders and customers, and translates complex medical and scientific information into accessible educational products.

Develop fraud and abuse detection models using large transaction, account, gameplay, and behavioral datasets. Responsibilities include data exploration, statistical and machine learning modeling, feature development with operations analysts, dashboard and monitoring creation, impact measurement, documentation, and presenting findings.

Develop and deploy production-ready machine learning models for game bots, intelligent NPCs, companions, world modeling, moderation, security, and QA automation. The role focuses on deep learning, computer vision, natural language processing, foundation models, reinforcement learning agents, reward design, policy optimization, data development, model evaluation, and scalable training environments. Candidates will collaborate with developers using agile practices and contribute to the roadmap for applied machine learning systems in gaming.

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.

Ph.D. interns apply machine learning and AI to semiconductor chip design or enterprise engineering tools. Responsibilities include developing ML models for EDA automation, placement, timing, power, and verification, or deploying LLM, RAG, and agentic systems. Interns will train, evaluate, and deploy models, conduct rigorous experiments, collaborate with engineering and technology stakeholders, assess production performance and safety, and present findings to leadership. The role requires doctoral research in AI, machine learning, computer science, electrical engineering, data science, or a related field.

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.

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.

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.