Top Machine Learning Jobs in Santa Cruz, CA

Manage paid media strategies and campaigns across search, social, display, and programmatic channels. Advise clients using integrated paid, organic, and analytics data; oversee campaign performance, keyword research, ad copy, landing page recommendations, and presentations. Build client relationships, mentor account associates, collaborate with SEO and data teams, and use AI to improve workflows and outcomes.

Develop and lead paid media strategies across search, social, display, and programmatic channels. Manage campaign strategy, performance analysis, testing, optimization, and integrated paid and organic recommendations. Consult with clients, present results, build relationships, mentor account associates, and identify data-driven growth opportunities. Use AI tools to improve workflows and contribute insights across the team.

Lead strategy to define, measure, and evolve Solution Engineer and Cloud Solution Architect excellence for Microsoft Security. Use data, AI-powered analytics, and customer insights to identify performance drivers, design capability strategies, advise senior leaders, and drive field transformation. Build governance, risk remediation, and scalable enablement programs while partnering across engineering, product, sales, and enablement to measure impact and continuously improve outcomes.

Design, build, and deploy production-ready intelligent solutions using machine learning, deep learning, generative AI, and large language models. Develop RAG pipelines, integrate AI services, manage model deployment and MLOps workflows, and apply strong software engineering practices. Collaborate with engineering, product, and data teams in a distributed environment to create scalable, reliable, responsible AI-powered products.

Leads AI-enabled Finance transformation initiatives from roadmap development through implementation and adoption. The role analyzes Finance processes, identifies automation opportunities, documents requirements, coordinates cross-functional Technology and Finance teams, manages change and training, tracks ROI and KPIs, and supports governance, compliance, SOX controls, and system integration across enterprise applications.

Develop HPC and AI software workflows for experimental data processing, imaging, plasma, high-energy physics, and materials simulations. Profile applications, benchmark performance, identify bottlenecks, and advise collaborators and product teams. Build tutorial examples, translate research into software tools, and represent NVIDIA at scientific conferences and industry events.

Designs statistical analysis plans and validates machine learning models using rigorous performance, calibration, uncertainty, subgroup, fairness, and longitudinal analyses. Applies biostatistical methods to healthcare data, documents assumptions and limitations for auditability and regulatory readiness, and translates complex findings into clinically meaningful insights. Collaborates with engineering, machine learning, data, clinical, and product teams.

Leads technical strategy and product adoption for major Retail and CPG enterprise accounts as Databricks’ primary technical voice. Partners with account executives, guides customers through data and AI transformations, builds technical champions, aligns solutions to business strategies, and mentors team members. Requires extensive pre-sales, big data, cloud, data science, programming, and production data systems experience.

Owns CareSource’s EDI platform vision, roadmap, backlog, and delivery. Translates healthcare, regulatory, and integration requirements into technical specifications; partners with engineering, architecture, QA, DevOps, trading partners, and business teams; coordinates releases and Agile delivery; monitors transaction performance, defects, SLAs, and platform telemetry; drives data quality, observability, automation, compliance, documentation, and continuous improvement across EDI capabilities.

Designs, integrates, tests, maintains, and upgrades complex IT systems across hardware, software, and security domains. The role validates system compliance, diagnoses issues, recommends improvements, and supports secure, reliable mission-critical environments. Responsibilities also include working with unstructured data using open-source tools, cloud computing, machine learning, and data visualization technologies, while collaborating with cybersecurity teams.

Leads the See & Scout engineering organization across software, data, machine learning, and robotics. Owns technical strategy, architecture, and multi-year roadmaps for scalable cloud, distributed data, edge, and machine learning platforms. Oversees the full data and ML lifecycle, production delivery, operational excellence, and customer-focused agricultural intelligence capabilities. Recruits and develops engineering leaders, partners cross-functionally, and aligns stakeholders across Blue River and John Deere.

Build and lead Nebius’s federal affairs function in Washington, D.C. Develop policy strategy across AI regulation, trade, energy, infrastructure, and national security; establish bipartisan relationships with Congress and executive agencies; represent the company in federal initiatives and coalitions; assess regulatory risks; coordinate with legal, communications, and infrastructure teams; manage outside lobbying partners; and hire staff as the function scales.

Develop and test AI software using large datasets, algorithms, and statistical analysis for industrial applications. Collaborate with machine learning and data engineers to build integrated AI/ML solutions, evaluate performance, monitor industry trends and regulations, and present progress to leadership and stakeholders. The internship offers hands-on experience, mentorship, and exposure to practical AI innovation.

Develop and test AI software for industrial applications using Python, JavaScript, and C++. Evaluate data, statistics, and algorithms; collaborate with machine learning and data engineers; support end-to-end AI/ML integration; monitor industry trends and regulations; and present progress to leadership and stakeholders.

Lead research, architecture, and production deployment of large-scale algorithms for budget pacing, bid optimization, and marketplace balancing in Yahoo’s DSP. Apply control theory, optimization, and machine learning to real-time systems, while establishing AI-augmented research and engineering workflows. Own multi-quarter initiatives, define evaluation frameworks, guide technical strategy, collaborate with product and engineering leadership, mentor scientists and engineers, and communicate complex research and architectural decisions to executives.

Lead the definition and evolution of cybersecurity technology platform and service offerings for cyber defenders and CISOs. Drive requirements through software and service lifecycles, deliver differentiated offerings to market, and guide cross-functional teams toward consistent, high-quality execution. The role requires deep expertise in at least two cybersecurity domains, managed services experience, strong communication skills, executive presentation ability, and awareness of AI’s impact on cyber defense.

Lead the vision, strategy, roadmap, backlog, delivery, adoption, and lifecycle management of an enterprise AI platform. Manage three direct reports and collaborate across technology, cybersecurity, risk, legal, compliance, data, and analytics. Ensure secure, scalable, governed, and responsible AI capabilities while translating business and technical priorities into measurable product outcomes. Drive stakeholder alignment, platform adoption, continuous improvement, executive communication, and team development in a highly regulated environment.

Leads Magellan Health’s enterprise data and analytics strategy, modernization, engineering, governance, business intelligence, and AI/ML enablement. Oversees data platforms, pipelines, quality, lineage, compliance, and reporting while partnering with clinical, operational, and financial stakeholders. Builds and develops a 30+ person organization, manages a $3M–$5M budget, oversees vendors, and presents investment cases to executive leadership. Drives transformation from a low-maturity environment to a governed, insight-driven enterprise data platform.

Manage paid social campaigns and full-funnel strategies across Meta, LinkedIn, TikTok, Pinterest, Snapchat, and other paid channels. Oversee client accounts, analyze performance, identify growth opportunities, build client relationships, and collaborate with SEO, creative, and analytics teams. Contribute to thought leadership, coach associates, maintain quality standards, and explore automation, AI, and LLM search visibility initiatives.

Leads and manages an applied machine learning team developing fraud detection and identity verification models. Responsibilities include people management, coaching, code review, production ML systems, model lifecycle ownership, experimentation, deployment, monitoring, fraud research, cross-functional prioritization, and communicating results. The role remains hands-on while partnering with Product, Engineering, Risk, and leadership to drive measurable business impact and shape future product strategy using machine learning and AI.

Leads an applied machine learning team and owns fraud detection and identity model strategy, development, deployment, monitoring, and iteration. Partners with Product, Engineering, Risk, and senior leadership to set priorities and deliver business impact. Provides technical mentorship, reviews code, guides modeling and architecture decisions, researches fraud patterns, develops ML capabilities, and shapes responsible AI use under data governance and security constraints.

Lead the strategy, design, deployment, and scale-up of AI-powered health products across the Global South. Own product roadmaps, execution, government-system integration, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, machine learning, program, and domain teams to deliver sustainable, measurable public-health impact.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.