Top Machine Learning Jobs in Santa Cruz, CA

Manage and mentor a team of machine learning and data engineers, overseeing ML model development, data pipelines, and collaborating with product teams on technical requirements.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

The Machine Learning Engineer will develop and optimize models for processing tax documents, mentor juniors, and collaborate across teams.

The MLOps Engineer will design scalable ML infrastructure, manage containerized environments, develop training pipelines, and implement CI/CD pipelines, ensuring model reliability and performance.

The Machine Learning Engineer will build MLOps pipelines, optimize model performance, and collaborate cross-functionally to integrate ML models into gaming environments.

Develop and deploy AI agents, integrating them with external systems and optimizing performance in multi-agent environments. Collaborate with product managers to align agent capabilities with business needs, exploring technologies in Generative AI and LLM orchestration.

The Staff Machine Learning Engineer will lead ML initiatives, develop AI systems, optimize pipelines, and mentor team members to automate healthcare processes.

The Machine Learning Scientist will design causal inference models, build measurement pipelines, and collaborate with Finance & Product teams to optimize subscription pricing strategies at Netflix.

As a Machine Learning Scientist, you will build and enhance forecasting models for Netflix's subscription business, collaborate with various teams, and improve statistical forecasting methods while considering external market signals.

Lead ML strategy and standards as a senior individual contributor: define ML infrastructure, tooling, and lifecycle processes; establish monitoring and feature patterns; partner across platform, data, and product teams; mentor data scientists and ML engineers to scale reliable production ML systems.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

Design, build, and scale ML and Generative AI systems. Develop applications using ML architectures and monitor model performance.

Build AI/ML-powered features across ClickHouse Cloud, designing scalable APIs, integrating inference systems and vector DBs, implementing frontend interfaces, and ensuring production-grade monitoring, versioning, and observability for model deployments.

As a Software Engineer, AI/ML GenAI, you will design and implement AI features, manage embeddings, and optimize AI systems for production deployment while collaborating with product and design teams.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

The Staff Machine Learning Engineer will develop AI/ML applications, collaborate with teams to implement models, and leverage a variety of technologies to enhance Twilio's customer support operations.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

Lead design and delivery of generative AI features end-to-end, prototype and productionize early-stage AI systems, set technical direction, mentor engineers, and collaborate with product and design to drive measurable product impact.

Drive measurement, causal inference, and experimentation to optimize content promotion and personalization. Build robust metrics, partner with product and engineering, surface discovery opportunities, and independently deliver high-impact analytics and ML solutions.

Design, implement, and optimize scaled lifecycle campaigns across email and in-product channels to drive activation, revenue, retention, and cross-sell. Use marketing automation, behavioral data, and ML techniques to personalize experiences, analyze performance, and collaborate across growth, product, sales, and data teams.

Design and implement credit strategies using data, machine learning, A/B testing and advanced analytics to optimize underwriting, pricing, and credit line decisions. Lead end-to-end analytics for credit card products, monitor portfolio performance, conduct root-cause analysis, partner cross-functionally, and communicate findings to stakeholders.

The Staff Product Manager will collaborate with research, engineering, and design teams to develop AI tools, define metrics, and enhance existing products based on user feedback and testing.

The Machine Learning Architect will design ML systems, manage Agile processes, automate software testing, and support AWS cloud applications for clients, while mentoring peers.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.