Top AI & Machine Learning Jobs

The Manager of Machine Learning Engineering will lead a team to develop and deploy scalable ML solutions, oversee project direction, and ensure responsible AI practices while fostering cross-functional collaboration at Disney.

The Machine Learning Researcher will develop and implement advanced ML models for EEG neural decoding, collaborate with experts, and publish findings.

As an ML Research Engineer, you'll design experiments, implement model architectures, and engineer scalable libraries to advance molecular simulations to support drug discovery.

Design, build, and secure AI/ML-assisted systems for systems engineering, architecture, security, and requirements generation. Create API accounts, design intuitive and widely accessible user interfaces, implement modular security and access controls, build export and integration features (including Microsoft Office and external management tools), and produce user training materials and lessons learned to improve AI/ML processes.

Build and own production AI systems for legal workflows, including retrieval, document understanding, agentic LLM systems, evals, and data pipelines. Collaborate with engineers, lawyers, designers, and customers to translate legal judgment into reliable, usable product behavior.

Lead 0→1 product development for Emerald Cloud Services: define vision, conduct customer discovery, set product requirements for AI compute provisioning and management, partner with engineering and GTM teams, and launch and scale cloud services for enterprise and AI customers.

Advise mid-market clients on technology and AI strategy, build 3-5 year IT roadmaps, engage C-suite to prioritize IT investments, design Microsoft-stack solution architectures, guide AI adoption and governance, optimize IT budgets/staffing, lead audits and special projects, and support pre-sales to generate consulting engagements.

As a research engineer, you'll train and evaluate large AI models, optimize inference throughput, and build data pipelines to enhance research and production workflows.

Work with S32 portfolio companies to deploy AI systems into production, partner closely with customers, and bridge engineering and production to drive product and company growth.

Lead the design of generative AI solutions and multi-cloud architectures, translating business use-cases into scalable systems for enterprise deployments.