Top Machine Learning Jobs in San Diego, CA

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Lead the development of machine learning systems for Cedar's Personalization Engine, focusing on ML modeling, MLOps, and team management to drive healthcare solutions.

The AI/ML Software Engineer will embed models into workflows, collaborating with teams to enhance AI applications and tools, focusing on automation and best practices.

The Staff Bioinformatics Scientist leads complex bioinformatics projects, analyzes data, develops algorithms, and mentors junior scientists to innovate in cancer diagnostic product development.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Senior Software Engineer will develop ML training pipelines, maintain cloud systems, and optimize the ML lifecycle for dental products.

The Senior ML Ops Engineer will build and maintain infrastructure for AI/ML at scale, manage machine learning models, and support team initiatives while ensuring code quality and engineering standards.

Lead the machine learning and personalization efforts at Babylist, managing a team focused on enhancing product recommendations, search, and revenue through ML initiatives.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

Join Wasabi as an AI Engineer intern to build scalable machine learning solutions. Responsibilities include maintaining ML pipelines, model integration, and collaboration with various teams to drive AI initiatives.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

Lead computational analysis of deep sequencing datasets (RNA-seq, ribosome profiling, CLIP-seq, SHAPE-seq, etc.), develop pipelines, interpret results in RNA biology and disease contexts, collaborate with experimental teams, present findings, and contribute to publications, patents, and strategy for genetic medicine programs.

The Implementation Specialist (CRM) will deliver CRM solutions, customize workflows, train staff, optimize processes, and ensure client engagement for dealer partners.

The Director of AI & Automation leads GT's enterprise-wide AI and automation strategy, driving initiatives to enhance operational efficiency and improve service delivery in a regulated environment.

The Vice President of Customer Success leads customer value initiatives, oversees onboarding and adoption of services, manages account strategies, and collaborates across departments to enhance customer experience and retention.

The Enrollment Advisor helps prospective patients through the onboarding process, providing information and support throughout their enrollment in Revero's program.

The Legal Intern will assist attorneys at Cambium Learning with various legal tasks, including compliance, governance, and intellectual property matters.

The SVP of AI Innovation - Web Scraping will lead the development of AI-driven web scraping strategies, focusing on data acquisition, technology enablement, compliance, team building, and cross-functional collaboration for new data services.

The Product Manager will identify process improvements and innovations, utilize automation and AI, and manage the product lifecycle to enhance productivity and deliver business value.

As an Applied Scientist, you will design and implement machine learning models, develop personalized systems, and enhance decision-making through AI technology to improve user experience and business operations.

The Lead Bioinformatics AI Scientist will lead AI and GenAI R&D initiatives to develop advanced clinical testing and genomic data analysis platforms, leveraging expertise in bioinformatics and machine learning.

As the Data Science Lead for Monetization, you'll shape monetization strategy, lead the data science team, and drive decision-making through measurement and experimentation.

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 the development of a new product area focused on improving onsite customer experiences using AI and machine learning to optimize marketing conversions. Oversee product strategy, measure performance, and collaborate with teams to ensure successful product launches.

As a Data Scientist, you will solve complex data problems using AI and machine learning, develop prototypes, and contribute to product strategy.