Top Senior Machine Learning Jobs in San Diego, CA

The Senior Machine Learning Engineer will build and enhance models and systems for classifying and enriching Internet data, collaborating with various teams to improve data quality and insights.

Lead the development and deployment of ML models to optimize pricing and enhance customer experiences. Drive AI strategies, conduct research, and collaborate across teams.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.

Serve as the presales technical expert for ML capabilities: lead discovery, architect ML solutions, run demos/workshops/proofs-of-concept, coordinate cross-functional teams, and inform product direction based on customer feedback.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

The Staff Software Engineer, AI/ML Focus will lead AI product development, ensure system reliability and security, and collaborate with cross-functional teams to innovate tools and products.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

Design, build, and operate production-grade ML systems for personalization, search, and recommendations. Own end-to-end pipelines from data ingestion and modeling to deployment, monitoring, and iteration, ensuring scalable, reliable, and observable services.

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

As a Senior Machine Learning Platform Engineer, you'll architect a scalable ML platform, collaborating with teams to ensure compliance, optimize performance, and guide best practices in ML workflows.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

Provide program management and IT systems analysis support to the NAVWAR Front Office, including strategic planning, process improvement, documentation, tracking program deliverables, automating workflows, integrating and visualizing data, developing prototypes and policy guidance, and supporting special projects using government-provided commercial IT tools.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.