Top Remote Machine Learning Jobs in San Diego, CA

The role involves delivering advanced analytics and machine learning solutions, collaborating with stakeholders, and mentoring junior data scientists.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

Seeking Applied Scientist to build scalable AI systems for estate planning, focusing on production-grade applications and document understanding using advanced AI models.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

The Senior Machine Learning Operations Engineer will build and operationalize the ML Ops platform to deploy and monitor machine learning models, focusing on infrastructure, automation, and integrating ML workloads within the AWS-native architecture.

Lead technical direction for AI across products, architect RAG services, mentor engineers, and ensure compliance in AI usage.

As a Senior Product Manager, you will lead the development of tools for financial advisors, focusing on product execution, advisor-centric development, and integrating AI into workflows while mentoring junior team members.

The intern will focus on developing and evaluating machine learning models for automated scoring of Spanish responses, collaborating with psychometricians and data scientists.

The intern will assist the machine learning team in modeling text for educational assessments, utilizing transformer models and traditional techniques while collaborating with psychometricians and data scientists.

As a Machine Learning Engineer in Computer Vision, you'll develop AI solutions using advanced algorithms, focusing on image classification, segmentation, and video processing tools.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

As an Associate Technical Architect in Machine Learning, you will design and develop advanced ML models on AWS, ensuring scalability and reliability while collaborating with cross-functional teams.

The Machine Learning Engineer will manage AI/ML projects on AWS, optimize data systems and databases, and enhance data architecture for predictive insights.

As a Staff Software Engineer, you will lead the development of Cake's AI platform infrastructure, focusing on building, operating, and improving ML systems. The role requires collaboration with customers to address ML challenges and enhance platform capabilities, emphasizing ownership and operational excellence.

The Machine Learning Engineer will design, build, and deploy ML models for data-driven products, collaborating with teams to optimize pipelines and improve performance.

As an intern, you'll assist in developing edge computing solutions, collaborate with machine learning teams, and improve data processing for satellites.

The AI & Machine Learning Director will lead client engagements, analyze corporate performance, and drive improvements in profitability through machine learning and data analysis, while also managing business development and team collaboration.

The Senior Vice President will lead projects focused on corporate performance, drive revenue growth, and develop business strategies while utilizing data modeling and machine learning techniques for analysis and solutions.

As a Staff Machine Learning Engineer, you'll develop, implement, and optimize ML models to enhance personalized customer experiences, collaborating across teams.

The role involves developing and maintaining machine learning models and infrastructure, defining technical vision, and leading cross-functional initiatives for scalable ML systems.

The role involves leading ML strategy, architecting systems, designing algorithms, collaborating with teams, and mentoring engineers in AI for enterprise analytics.

Lead the design and scaling of ML infrastructure, work on model lifecycle, optimize workflows, and mentor engineers in a fast-paced AI environment.