Top Machine Learning Jobs in San Diego, CA

The VP of AI will lead the integration of AI into products, drive strategy for AI initiatives, and ensure responsible implementation across the organization.

Lead mobile app attribution strategies, collaborating with teams across engineering and data analytics to optimize performance and feature implementation.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

Develop and implement messaging and positioning for AI products, create marketing content, lead go-to-market strategies, and analyze market research.

The Senior Product Manager will advance fraud detection capabilities, manage product lifecycles, develop requirements, and collaborate with engineering and data science teams.

The Senior Principal Product Manager will define the product strategy for ExtraHop's RevealX platform, focusing on enhancing SOC workflows and leading cross-functional execution while mentoring peers and aligning product vision with business goals.

Own and close enterprise customer deals, develop expansion opportunities, educate customers on AI architectures, engage with multiple stakeholders, and collaborate with product and engineering teams.

The role requires leading AI business strategy and advising C-suite executives on AI products to enhance adoption and business outcomes, including creating actionable insights and conducting market research.

The VP Analyst will provide insights to C-level clients on enterprise application services and AI capabilities, conduct research and analysis, and develop thought leadership content while advising clients on strategies and implementations.

The Product Manager Insurer Experience will enhance the Insurer experience on the AI Risk Exchange platform by identifying opportunities, collaborating with teams, and delivering high-impact solutions that drive value for third-party insurers.

The Quantitative Mortgage Lending Analyst will analyze mortgage lending data, enhance analytics tools, integrate performance metrics, and collaborate on lending strategies.

Lead data science initiatives, mentor junior scientists, and apply machine learning to influence enterprise decision-making and improve business outcomes.

The Enterprise Account Executive will drive the sales of Sift's fraud solutions to Fortune 1000 companies, engaging with key stakeholders and building custom strategies to address fraud challenges through value-based selling and collaboration.

Lead AI transformation initiatives in procurement, creating impactful research, developing strategies, and advising clients on AI integration and analytics for business outcomes.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Lead the design and deployment of RL post-training systems, aligning model behavior with user value and business objectives, while mentoring applied scientists and engineers.

The role involves designing and prototyping advanced AI reasoning systems for real estate, focusing on LLM-powered applications while mentoring junior scientists.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

As a Machine Learning Intern, you'll prototype and evaluate ML systems, collaborate with teams, and analyze large datasets to improve user experiences.

The Principal Software Engineer will lead the development of autonomous systems for satellites, overseeing architecture and capabilities while mentoring engineers. Responsibilities include guiding algorithms for satellite operations and ensuring software integration across mission elements.

Develop network automation software for TeraWave satellite communication systems, focusing on embedded software, network protocols, and real-time processing.

As a Principal Machine Learning Engineer, you will develop multimodal AI experiences, design agent interactions, and lead cross-team initiatives while ensuring AI safety and reliability.

Lead the development of agentic AI systems for real estate, focusing on long-horizon, supervised experiences. Architect collaborative systems and define success metrics while mentoring a small team.

Lead product strategy for AI-driven security operations, defining the vision and roadmap for agentic workflows, collaborating with teams, and measuring success metrics.