Top Machine Learning Jobs in San Diego, CA

This role involves defining and leading biopharmaceutical bioinformatics strategy, overseeing computational biology tasks in oncology and immunology, and collaborating across various scientific functions to support clinical development programs.

As a Research Scientist Intern, you'll work on machine learning problems, prototype features, write production code, and collaborate with mentors.

The AI Program Manager designs and implements AI programs, engages stakeholders, and manages project risks in a multi-disciplinary environment.

The AI Program Manager designs and manages AI programs, coordinates projects, engages stakeholders, mitigates risks, and leads teams with minimal guidance.

As a Senior Product Manager for the insurance marketplace, you will manage integrations, optimize performance, ensure data accuracy, and improve user experience in quoting.

Lead product management efforts at Genesis Molecular AI by defining product roadmaps, collaborating across teams, and ensuring execution of projects in drug discovery.

The Sr. Manager, Sales Enablement will optimize digital sales workflows in diagnostics, focusing on program design, sales strategy, learning development, and technology implementation to increase productivity and efficiency.

The Principal Deep Learning/AI Engineer will design and implement AI methods in bioinformatics, ensuring scientific soundness and production readiness while mentoring team members and leading technical design reviews.

As a Principal Machine Learning Scientist, you will conduct research, analyze data, develop models, and lead projects to implement innovative solutions in real estate.

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.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

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.

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

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 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.

The Senior Technical Program Manager will oversee the delivery of complex projects related to Application Modernization, working closely with multidisciplinary teams, driving programs forward, and balancing product goals with engineering constraints.

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 Engineering Manager will lead a team of Data Scientists and ML Engineers to build a Dispatch Optimization platform, focusing on model deployment and operational excellence.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.