Top Remote Machine Learning Jobs in Santa Cruz, CA

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

Lead delivery of advanced analytics and investigative support for federal programs. Manage multiple concurrent projects, schedules, costs, risks, personnel, vendors, and stakeholder communications to ensure quality, timely contract-aligned deliverables.

Lead the implementation of AI-driven supply chain solutions, collaborating with clients to enhance their business processes and ensure seamless technology integration.

Lead strategy and roadmap for DTNs upstream intelligence portfolio, especially Farm Intelligence. Conduct customer discovery, define product metrics, prioritize features, and partner with Engineering, Design, Data Science, and Commercial teams to deliver data-intensive, AI-enabled B2B SaaS products. Drive launches, adoption, and continuous optimization through experimentation, analytics, and stakeholder alignment.

Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients, guiding architecture and mentoring engineers.

Design and run partner presales enablement programs that build hands-on technical proficiency across ISV and C&SI partners. Own curriculum, assessments, roadmaps, KPIs, and large-scale learning events; coach trainers; align cross-functionally to drive partner-sourced pipeline and certification outcomes.

Define and execute Americas logistics and warehousing strategy; lead multi-site DC operations, inbound/outbound logistics, carrier management, trade compliance/imports, P&L oversight, WMS/TMS/ERP optimization, and AI/automation adoption. Requires cross-regional enablement and ~25-40% travel.

Lead operationalization of AI strategy by implementing scalable AI platforms, standards, and governance. Identify and prioritize high-impact AI and analytics use cases, drive end-to-end delivery into production, embed AI into business processes, manage AI teams, mentor practitioners, and evaluate emerging AI/GenAI technologies to ensure responsible, secure, and measurable business impact.

Lead the architecture, implementation, integration, and optimization of Oracle EPM Planning solutions. Design planning, budgeting, forecasting, modeling, security, metadata, and reporting frameworks; configure Oracle EPM modules; and apply AI-driven forecasting capabilities. Lead requirements workshops, testing, deployment, stakeholder presentations, and pre-sales activities. Mentor consultants and developers while advising finance and executive stakeholders on enterprise planning transformation initiatives.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

Leads data science strategy across Mexico and Brazil, manages and mentors a distributed team, and remains hands-on building and deploying machine learning models. Establishes modeling standards, infrastructure, delivery practices, and technical roadmaps while partnering with credit leadership on underwriting, valuation, impact measurement, and P&L analysis. Requires strong applied machine learning expertise, prior data science leadership, business communication skills, and understanding of credit or underwriting.

Own the technical architecture, strategy, and roadmap for an autonomous construction robotics stack spanning localization, planning, controls, and safeguarding. Make build-versus-reuse-versus-buy decisions, design safety systems, guide integration and field validation, establish shared technical foundations across autonomy programs, and mentor engineers. The role requires architecting and shipping production autonomous systems, strong compiled-language software skills, broad systems judgment, and 10+ years of relevant experience.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.

Leads enterprise sales strategy and revenue growth for AI-powered eDiscovery, legal technology, compliance, analytics, and data intelligence solutions. Builds pipelines, manages complex consultative sales cycles, develops executive client relationships, expands strategic accounts, and positions responsible AI adoption. Partners with product, operations, legal, security, marketing, and executive teams on solution development, pricing, contracts, implementation, and market expansion across corporations, law firms, government, and regulated industries.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Leads technical solution development for military and federal health capture and proposal efforts. Designs secure cloud, DevSecOps, EHR modernization, interoperability, data, and analytics architectures; develops technical volumes, graphics, compliance matrices, staffing estimates, demonstrations, and presentations. Ensures security and compliance alignment, supports pricing strategy, collaborates across capture and delivery teams, and mentors architects and subject-matter experts.

The AI Executive Partner will advise C-Suite executives on leveraging AI to drive business outcomes, manage member relationships, and deliver innovative AI solutions.

Oversee development, validation, monitoring, and governance of consumer credit risk models used for loss forecasting, credit decisioning, regulatory reporting, and risk management. Apply statistical, econometric, and machine learning methods to PD, LGD, and EAD models; support CECL, stress testing, and macroeconomic scenario analysis. Assess model performance, data quality, and compliance while communicating findings to senior leaders, auditors, regulators, and other stakeholders.

Serves as the technical and business advisor for Verint’s Open CCaaS platform, selling CX automation solutions to C-suite customers. Builds executive relationships, communicates ROI, leads cross-functional product and sales teams, identifies expansion opportunities, and delivers thought leadership. Requires expertise in AI, data science, contact center operations, data architecture, and cloud platforms, with approximately 30–50% travel.

Leads strategy, roadmap, development, and adoption of analytics and AI products for Ford Integrated Services. Owns reporting platforms, dashboards, governance, metrics, support models, and generative AI initiatives. Partners with senior stakeholders and cross-functional teams including engineering, design, data science, and analytics to deliver actionable insights, improve subscriptions performance, and establish trusted business intelligence solutions.

Own product areas for an autonomous banking platform, translating backend capabilities (APIs, async workflows, ML) into user-facing features. Conduct customer discovery, define technical requirements and acceptance criteria, prioritize backlog, partner with engineering on scoping and de-risking, and validate outcomes using feedback loops and analytics.

Build Quince’s greenfield, AI-native supply chain planning platform from architecture through production. Own forecasting and optimization model pipelines, experimentation, deployment, monitoring, operator tooling, integrations, and AI-augmented workflows. Partner with scientists, planners, business leaders, and distributed engineering teams to translate supply chain needs into scalable systems. Set technical direction, establish engineering standards, and recruit and develop a high-performing team.

Lead and grow a data science team focused on customer intelligence, personalization, product analytics, marketing optimization, and customer lifetime value. Develop predictive and segmentation models, analyze web and mobile engagement, design experimentation programs, and apply causal inference, survival analysis, forecasting, Bayesian methods, NLP, and machine learning. Partner with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into scalable products, actionable recommendations, and measurable business impact.

Leads a backend engineering team responsible for scalable, reliable systems. Balances people management, technical direction, architecture, and execution; hires, coaches, and develops engineers; guides complex initiatives from design through production; and partners with Product and Engineering stakeholders to improve system reliability, performance, maintainability, and team productivity.