Top Machine Learning Jobs in San Diego, CA

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.

The Talent Researcher role involves building talent maps in AI, ML, and voice technology, translating hiring signals into research plans, and delivering market intelligence to enhance recruitment processes.

The Staff Advanced Analyst will drive data analytics to improve CS Safety experiences, influence product decisions, and build measurement tools using data-driven insights.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The role involves leading a team to manage data strategies and analytics for Netflix Games, requiring expertise in data science, business analytics, and team management.

Lead Data Scientist responsible for creating ML-driven risk assessments and AI workflows within a SaaS security platform, ensuring effective decision-making and system reliability.

The Brand Marketing Manager will develop content strategies for lead generation, produce high-quality marketing assets, collaborate with the Demand Generation team, and analyze data to optimize campaigns.

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

Lead the Ad Ranking team, focusing on improving ad quality and performance using machine learning. Responsibilities include team management, stakeholder collaboration, and executing analytical initiatives.

The role involves analyzing biobank datasets using statistical and computational methods, developing machine learning pipelines, and collaborating with scientific teams to advance research in human genomics.

The Product Marketing Manager will execute product launches and support go-to-market initiatives, collaborating with cross-functional teams to develop and deliver messaging and enablement materials targeting both technical and business stakeholders.

The Staff Software Engineer, AI role involves defining technical direction for AI applications, mentoring engineers, and enhancing patient-provider interactions through advanced language and voice technologies.

Lead product strategy and development in cybersecurity, focusing on supply chain security solutions. Engage with customers and cross-functional teams to drive product innovation and performance metrics.

As a QA Engineer, you'll validate features, handle bug fixes, leverage AI for QA workflows, and enhance test automation across multiple product teams.

The AI Design Engineer leads AI solutions development for nuclear and energy sectors, focusing on model implementation, performance validation, and integration with existing systems.

Lead and grow the engineering team, architect the core AI platform, manage data infrastructure, and drive best practices in software development.

As Head of Product, you will define the product vision and execute strategy for an AI-driven logistics billing platform, focusing on customer discovery, AI integration, and team leadership.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.

Lead and scale Zapier's AI/ML organization by defining strategy, delivering ML products and platforms, coaching teams, enabling product partners, and ensuring safe, reliable, cost-effective model deployment and operations.

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 Data Science Actuary role involves building and maintaining rating systems and risk models, conducting analysis for underwriting and operations, and integrating new data sources while collaborating with multiple teams.

As a Principal Software Engineer, you will lead multi-team initiatives, influence technical strategy, and ensure the quality of complex systems, mentoring engineers and collaborating with senior leadership to align on business goals.

The role involves managing a client portfolio of Chief Data Officers, delivering insights on data strategy and analytics, mentoring clients, and fostering collaboration with internal teams to ensure client satisfaction and retention.

The Generative AI Analyst will create prompts and responses for machine learning projects, lead labeling initiatives, and provide training on best practices for LLM datasets.