Top Machine Learning Jobs in Santa Cruz, CA

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

As a Staff Machine Learning Engineer, optimize card pricing models, lead ML lifecycle, collaborate with experts, and enhance predictive features.

The Machine Learning Engineer will design and deploy computer vision models, build training pipelines, and enhance ML infrastructure to improve agricultural field operations.

The role involves designing and supporting GPU/Kubernetes clusters for AI/ML workloads, developing automation tools, and troubleshooting infrastructure issues.

As an AI/Machine Learning Intern, you will contribute to software applications and AI projects, working with data engineers and researchers to implement innovative solutions.

The intern will work on AI projects, gaining hands-on experience in software development, algorithm evaluation, and collaboration with engineers to enhance AI capabilities.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

The Staff Software Engineer, AI/ML Focus will lead AI product development, ensure system reliability and security, and collaborate with cross-functional teams to innovate tools and products.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

This role involves defining and managing the AI platform's roadmap, collaborating with cross-functional teams to integrate AI capabilities, and ensuring product quality and reliability metrics.

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

Design and deliver scalable AI solutions powered by Large Language Models. Collaborate with teams to create cloud-native architectures, enable knowledge discovery, and mentor engineers in AI initiatives.

Lead technical direction and execution of Lime's CX automation platform, building scalable backend services, decision engines, and human-in-the-loop workflows to automate rider issue resolution while enforcing fraud and trust guardrails and improving operational metrics.

Design, build, and maintain scalable AI/ML architectures; collaborate with data scientists, engineers, product, and compliance to integrate models; evaluate tools and processes; monitor performance and ensure industry-standard compliance and ethical practices.

Design, build, and operate production-grade ML systems for personalization, search, and recommendations. Own end-to-end pipelines from data ingestion and modeling to deployment, monitoring, and iteration, ensuring scalable, reliable, and observable services.

Design and build agentic AI workflows for biological and clinical data curation and analysis. Implement context engineering (RAG variants), prompt and agent architecture optimization, LLM tool-use integrations, and evaluation benchmarks. Collaborate with bioinformatics and clinical experts to translate domain problems into reliable, production-quality agentic systems.

Build and own ML platform infrastructure and tooling to enable model development, deployment, monitoring, and iteration. Lead realtime model monitoring, experiment tracking, reproducibility, and operational reliability to scale fraud-prevention ML systems in production.

Lead architectural design of AI/ML solutions, mentor staff, and ensure data governance compliance in high-scale enterprise environments.

The Senior ML Engineer will develop and optimize machine learning solutions for audience intelligence, build production pipelines, and collaborate with cross-functional teams to enhance user engagement and revenue.

Manage AI/ML projects from Proof of Concept to Minimum Viable Product using Agile methodologies while ensuring stakeholder communication and project alignment.