Top Remote Machine Learning Jobs in San Diego, CA

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 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.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

As a Staff AI Engineer, you'll design and implement components of an AI tutoring system, conduct experiments, and create scalable systems integrating LLM capabilities, ensuring high-quality learning experiences.

As a Senior Machine Learning Engineer, you'll develop models for risk identification, collaborate cross-functionally, and deploy ML solutions, ensuring performance monitoring and continuous improvement.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

The Business Analyst 2 analyzes AI-powered data solutions, optimizes customer experience automation, and collaborates with teams to drive business insights and value.