Top Machine Learning Jobs in San Diego, CA

As a Staff Software Engineer - ML, you will develop and manage relevance models to enhance user experience on Eventbrite. Collaborating with various teams, you will tackle machine learning, search ranking, and recommendations to ensure the right content is presented to users.

The Practice Manager for Data Science, AI, and ML will lead a team of experts to deliver professional services, ensuring successful customer engagements. Responsibilities include acting as a technical liaison, guiding teams through projects, educating clients on data science solutions, and supporting cloud migrations. The role requires building strong customer relationships and delivering training to ensure client and team knowledge.

The Technical Product Manager will collaborate with data science and machine learning engineers to develop models optimizing ad performance. Responsibilities include integrating ad infrastructure, communicating with stakeholders, monitoring KPIs, and leveraging insights for product decisions.

As a Staff Data Scientist at Coinbase, you will build advanced models, provide technical mentorship, and develop novel experimentation techniques to drive business value. Your role will involve creating sequential features based on user behavior and quantifying the impact of negative experiences on the platform.

The Machine Learning Engineer is responsible for developing, implementing, and productizing machine learning models for business solutions. Key tasks include model deployment, data preparation, collaboration with product teams, optimization, monitoring, and staying current with AI/ML trends.

As a Senior Technical Program Manager at Coinbase, you will lead efforts in customer self-service and automation by identifying opportunities for enhancement, developing long-term strategies, and collaborating with cross-functional teams. You'll focus on improving customer workflows and implementing scalable automation solutions.

The Senior Principal AI/ML Engineer will lead the development of machine learning and generative AI solutions, collaborate with cross-functional teams, mentor engineers, and guide technical direction. Responsibilities include designing scalable applications and contributing to advanced analytics platforms, ensuring successful delivery of data-driven decisions.

The Principal Engineer for the ML Training Platform will lead a team to enhance the ML training and evaluation process. Responsibilities include designing and maintaining scalable ML data processing solutions in AWS using Kubernetes, optimizing model performance with GPUs, and collaborating with various teams to ensure the effective execution of technical initiatives.