Top Machine Learning Jobs in San Diego, CA

Lead AI/machine learning innovations and advanced analytics for new vehicles. Develop statistical models for pricing and valuation, guiding experiments and communicating insights.

The Senior Data Scientist will design and implement data-driven initiatives, optimize product offerings using AI/ML, and collaborate with engineers on scalable solutions.

Lead and manage a team of engineers in developing Affirm's Fraud Decisioning System, focusing on innovation and cross-functional collaboration with various stakeholders.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

As a Machine Learning Intern, you'll prototype and evaluate ML systems, collaborate with teams, and analyze large datasets to improve user experiences.

As a Senior Software Engineer, you'll enhance servicing decisions with ML models, improve experimentation, and scale decisioning systems for personalized borrower experiences.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

Research Scientist at Upstart will develop machine learning models to enhance borrower risk predictions, design prototypes, and collaborate with cross-functional teams while mentoring junior members.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

The Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Innovation Engineer will design and implement AI systems for water management, collaborating with cross-functional teams to improve efficiency and automation.

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.

The Talent Researcher role involves building talent maps in AI, ML, and voice technology, translating hiring signals into research plans, and delivering market intelligence to enhance recruitment processes.

The Brand Marketing Manager will develop content strategies for lead generation, produce high-quality marketing assets, collaborate with the Demand Generation team, and analyze data to optimize campaigns.