Top Senior Machine Learning Jobs in San Diego, CA

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

Lead technical strategy and architecture for machine learning systems, mentor engineers, and design scalable solutions for data mining and real-time inference.

The Director of Data Engineering, ML & AI leads data strategy and AI capabilities, managing a team to enhance data infrastructure, machine learning systems, and sustainability analytics while driving company-wide AI 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 Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

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

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.

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.

The Sr. Data Engineer will architect and build an end-to-end data platform, developing data pipelines and infrastructure for AI and robotics teams, ensuring data integrity and governance, and collaborating on ML model development.

The role involves developing and deploying machine learning models for forecasting within the Camus platform, requiring collaboration and technical depth in ML.

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

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.

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 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 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.

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

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, 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.

Design and maintain datasets, build and evaluate domain-specific ML and vision-language models for real-time privileged access threat detection; deploy and optimize Python/Docker inference services integrated with WebSocket/WebRTC and protocol-level interfaces; monitor and document production models.

The Senior ML Engineer will develop and optimize machine learning solutions for audience intelligence, build production pipelines, and collaborate with cross-functional teams to enhance user engagement and revenue.

Seeking a Senior Machine Learning Engineer with expertise in Generative AI and MLOps to design and maintain AI solutions for telecom, focusing on performance and scalability.

As a Staff Machine Learning Research Scientist, you will lead ML research, develop evaluation frameworks, mentor researchers, and collaborate on clinical AI solutions.