Top Remote Machine Learning Jobs in Santa Cruz, CA

Lead the development and execution of a personalization strategy to enhance customer engagement and retention. Manage a team and leverage AI-driven technology to innovate the customer experience across multiple channels while measuring success with KPIs.

The Technical Project Manager will coordinate technical projects related to deep learning frameworks, managing timelines and risks while ensuring client satisfaction. Responsibilities include leading project meetings, collaborating with various stakeholders, and maintaining project quality standards.

The role involves managing data to uncover insights, developing predictive models, and bridging clients with data intelligence within the context of evolving market research methodologies.

The Enterprise Account Executive is responsible for defining and driving product-led sales, managing the sales process for new accounts, understanding customer technical challenges, and articulating value propositions.

As a Senior to Principal Machine Learning Engineer, you'll lead the architecture and development of the Agentic AI platform, focusing on LLMs. Responsibilities include enhancing LLM performance, designing evaluation methodologies, and establishing safety protocols for LLM use.

The Data Analyst will prepare and analyze data for predictive modeling, support multiple projects, and collaborate with various teams to enhance data processes and insights.

Lead the Ads Measurement & Impact Science team at Netflix, focusing on building first-party measurement solutions and driving analytics initiatives to enhance ad performance and insights.

The Engineering Manager leads a team to develop technology solutions for financial advisors, promoting agile practices and collaboration while driving continuous improvement and innovation.

The Workday HCM Architect leads the development of HR solutions utilizing Workday AI, Talent Management tools, and enterprise software implementation in collaboration with business and IT partners.

As Director of Data Science, you will lead predictive solutions and analytics for marketing, sales, and product development, mentor teams, and establish data-driven strategies aligned with business objectives.

The VP, AI Enablement will lead strategy and implementation of AI technologies in educational products, drive innovation, and collaborate with stakeholders to enhance learning outcomes.

Lead a team of engineers to design, develop, and enhance the data ingestion platform, focusing on real-time data processing and system reliability.

Lead research and development of advanced machine learning solutions, optimizing large-scale infrastructure and providing technical guidance on high-impact projects.

As the Engineering Manager, you will lead a product engineering team, influencing technical design, product delivery, and team growth while collaborating across functions and focusing on operational quality in payment solutions.

As a Senior Data Scientist at Ensemble, you will develop advanced AI and machine learning models, focusing on generative AI and predictive analytics to improve healthcare outcomes.

The Senior Risk Management Analyst will assess and mitigate risk in a merchant portfolio using financial analysis and AI technologies, enhancing underwriting decisions.

Lead the development and deployment of machine learning and generative AI models to enhance customer onboarding processes, utilizing data science techniques and cloud infrastructure.

The Implementation Manager will oversee the complete implementation process for new clients, ensuring efficient onboarding and alignment with customer needs while collaborating with internal teams.

The AI Application Engineer will design and deploy AI systems, collaborate with teams, implement Generative AI solutions, and promote continuous learning in AI practices.

The Business Operations Associate will drive data-driven decisions for business initiatives, lead A/B testing, and optimize processes to enhance customer acquisition and growth.

The Machine Learning Engineer role involves designing, implementing, and deploying ML solutions, focusing on LLMs and collaboration with engineering teams.

Responsible for building globally distributed ML ecosystems, developing data pipelines, implementing microservices, and collaborating across teams to enhance machine learning technologies.

Lead R&D to design and deploy ML models for conversational agents, enhance automation in customer support, and build scalable AI systems across business units.

The role involves building awareness of technologies, mentoring talent, promoting a culture of engineering excellence, and collaborating on critical business issues.

Support and scale customer onboarding for Togal.AI's cloud platform by providing training and assistance to maximize customer engagement and satisfaction.