Top Remote Machine Learning Jobs in Santa Cruz, CA

The Staff Research Scientist will conduct AI research, innovate in LLM and information retrieval, and collaborate with research teams.

The Engineering Manager, Machine Learning will lead a team focusing on 3D deep learning and computer vision, manage the ML roadmap, and implement best practices for MLOps pipelines.

As a Research Scientist Intern, you'll work on machine learning problems, prototype features, write production code, and collaborate with mentors.

The Senior Industry Marketing Manager will drive marketing strategy for AI/ML, develop initiatives, create content, and collaborate with sales teams.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Lead the development of machine learning systems for Cedar's Personalization Engine, focusing on ML modeling, MLOps, and team management to drive healthcare solutions.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Senior Software Engineer will develop ML training pipelines, maintain cloud systems, and optimize the ML lifecycle for dental products.

The Senior ML Ops Engineer will build and maintain infrastructure for AI/ML at scale, manage machine learning models, and support team initiatives while ensuring code quality and engineering standards.

Lead the machine learning and personalization efforts at Babylist, managing a team focused on enhancing product recommendations, search, and revenue through ML initiatives.

The Director will lead Macmillan's corporate social media and community growth strategy, enhancing engagement and driving measurable growth across digital platforms through strategic content and analytics.

Lead the design and optimization of programmatic bidding systems, collaborating with engineers and applying analytical methodologies to enhance performance.

The Director of Machine Learning Engineering is responsible for leading AI strategy, overseeing ML solutions, driving innovation, building teams, and ensuring operational excellence in ML systems.

The AIML Director will define the enterprise strategy for AI, Machine Learning, and Generative AI, leading architecture design and delivery of innovative solutions while mentoring a high-performing team.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

The Vice President, Employer Business Development & Sales will lead and expand a new business group, focusing on sales and relationships with self-insured employers and brokers, utilizing advanced analytics in healthcare benefits management.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

Lead product managers overseeing distribution and onboarding experiences, drive product execution, manage a team, and advocate for user needs.

Lead technical pre-sales engagements, design tailored solutions, demonstrate platform capabilities, assess customer needs, and expand relationships within life sciences and health technology.

The role involves leading strategic AI partnerships, driving revenue growth, and managing cross-functional teams while advocating for AI initiatives internally and externally.