Top Machine Learning Jobs in San Diego, CA

The Senior Product Manager will lead the strategy and execution of AI-driven features in a SaaS platform, ensuring high-quality user experiences and data-driven decisions while mentoring junior team members.

As an ML Engineer, you will build and deploy machine learning models for autonomous robots, collaborating with ML scientists and engineers to enhance AI capabilities.

Lead ML projects to optimize search and recommendations at Airbnb, collaborating with cross-functional teams to enhance user experience and business impact.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

As a Machine Learning Engineer, you will build LLM-powered agents, collaborate on experiments with LLMs, and implement AI features in production.

Design, develop, and deploy machine learning systems, improve ML infrastructure, and partner with stakeholders to enhance data science workflows.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

Develop and deploy ML models for personalization and optimization, analyze performance, and collaborate with product teams to enhance user experiences.

As a Machine Learning Engineer, you'll build scalable ML systems for personalized recommendations, collaborating with data scientists and cross-functional partners.

The role involves building scalable AI features, optimizing machine-learning pipelines, evaluating LLM outputs, and ensuring compliance with data governance standards.

The Senior Machine Learning Engineer will develop ML platforms, optimize model lifecycles, lead initiatives, and maintain code quality, collaborating with Data Science teams.

Lead the design and development of AI solutions, optimize algorithms, collaborate with teams, and develop advanced models to drive business insights.

Lead the design and implementation of GPU compute clusters for deep learning and HPC workloads, ensuring effective resource utilization, and supporting researchers' needs.

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

The Senior Full Stack Engineer will develop AI/ML features in ClickHouse Cloud, integrating databases with AI capabilities, ensuring robust API design, and building user-friendly interfaces.

As a Senior Data Engineer, you'll build a cloud-native Data Platform in Azure, design data pipelines, and collaborate with data scientists on AI/ML applications.

As a Senior Data Engineer, you'll build a data platform in Azure, design and implement data pipelines, develop cloud microservices, and mentor engineers while working with AI models.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

This role involves designing, developing, and scaling machine learning systems for payment flows and recommendations, leading technical initiatives, and optimizing complex financial decision systems.

Lead ML research and development, collaborating with engineers and clinicians to create enterprise-grade products and establish a research agenda while sharing insights through publications and presentations.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

The Applied Scientist Intern will develop and deploy AI models, build ETL pipelines, and collaborate to enhance AI quality in legal tech.