Top Machine Learning Jobs in San Diego, CA

Develop AI/ML-powered features in ClickHouse Cloud, focusing on frontend and API architecture, UI/UX, and integrations with AI systems.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

The Senior Machine Learning Engineer will manage the lifecycle of ML models, transform prototypes to production code, build training pipelines, and monitor system performance.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

As a Senior Machine Learning Engineer, you will develop and deploy AI-driven products to enhance clinical trials, collaborating with teams to improve patient care through scalable machine learning solutions.

The Staff ML Research Scientist will lead research in deep learning for drug discovery, develop innovative models, and integrate them into commercial software. Responsibilities include mentoring junior researchers and contributing to scientific publications.

The Senior Principal AI/ML Architect will drive AI architectural vision, influence multi-squad strategy, design intelligent systems, and set operational standards for Yahoo Mail's AI capabilities.

The Specialist Solutions Architect will guide customers in architecting ML & AI applications, provide advanced technical support, and collaborate cross-functionally to enhance Databricks' AI offerings.

Work on vision-language model development and infrastructure: improve VLM understanding, OCR and function-calling workflows, fine-tuning recipes, evaluation and robustness, and optimize training/serving pipelines. Own end-to-end projects from experiments to production-ready code, collaborating on scale, cost, and reliability.

The Associate Director, AI/ML Engineering will lead the development and deployment of AI solutions, manage multi-agent systems, and collaborate across functions to optimize AI/ML processes within a biopharmaceutical context.

Design and productionize ML models and agentic systems for intraday financial alpha generation. Build data pipelines, experiment frameworks, and portfolio optimization methods. Collaborate with quants and engineers to move models from research to live trading environments.

As a Senior Machine Learning Engineer, you will drive AI initiatives, collaborate across teams, and develop scalable ML infrastructure to improve healthcare.

The role involves collaborating with customers to solve engineering challenges using machine learning, develop solutions, train teams, and improve products based on feedback.

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

The AI Strategist leads AI initiative ideation and planning, collaborates across departments to define use cases, and ensures alignment with strategic and regulatory goals.

As a Machine Learning Engineer, you'll design and implement detection systems, enhance model efficacy, and analyze datasets to improve email detection against security threats.

As a Staff Machine Learning Engineer at Twilio, you will build and maintain data pipelines and ML infrastructure, ensuring high-quality data and model performance while collaborating with product and security teams.

Lead GoDaddy's three-year Generative AI and ML roadmap, architecting and scaling agentic and personalized AI solutions globally. Own end-to-end ML systems, enable rapid experimentation, ensure governance/compliance, and partner across product, engineering, and analytics. Mentor and grow high-performing teams and drive adoption of advanced AI techniques to improve customer experiences and business outcomes.

Design, train, and deploy ML models for Qur'ān recitation, tajwīd detection, and ASR. Build data pipelines for cleaning, segmentation, labeling, and evaluation. Integrate real-time predictions via APIs or lightweight on-device inference, optimize models for speed and mobile performance, and collaborate with backend developers to ship AI features in the app.

Research and build efficient ML systems for large-scale LLMs and agentic RL: design algorithms and system techniques, prototype in training/inference stacks, run large-scale experiments, and translate findings into production or publications.

Develop and prototype learning-based models using data-centric techniques; design and maintain multi-modal data and feature extraction pipelines; build auto-labeling systems; perform ETL and optimize SQL for analysis/ingestion; collaborate with data infrastructure and ML engineers to integrate workflows; write maintainable code and participate in code reviews to support scalable ML production.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

As a Senior ML Engineer, you will lead the design and operation of GenAI solutions, focusing on LLM development and deployment, mentoring colleagues, and collaborating with cross-functional teams to enhance AI capabilities for the insurance sector.