Machine Learning Jobs in Tempe, AZ

Develop CRM marketing strategies for Seller and Owner audiences using segmentation, personalization, customer journey analysis, statistical modeling, and machine learning. Measure campaign effectiveness through KPIs and analytical frameworks, identify engagement and retention opportunities, and communicate actionable insights to technical and non-technical stakeholders. Collaborate with Marketing, Data Engineering, and IT teams on data quality, infrastructure, and tailored analytical solutions.

Leads the design, development, deployment, and scaling of production AI/ML solutions for healthcare. Builds cloud-based machine learning systems, data pipelines, feature workflows, and MLOps processes including CI/CD, monitoring, drift detection, retraining, and governance. Provides architecture guidance, technical leadership, mentorship, and cross-functional partnership while applying NLP, deep learning, computer vision, foundation models, and other advanced AI techniques.

Lead the Forward Deployed AI Engineering team to build solutions, engage customers, and enhance cybersecurity with AI tools and data science.

Leads financial planning, budgeting, forecasting, reporting, business intelligence, and finance transformation. Develops financial models, executive dashboards, KPI frameworks, and variance analyses while improving data governance, automation, and AI-enabled forecasting. Partners with executives and departments on strategic decisions, business cases, M&A, and performance improvement. Builds and manages a high-performing FP&A and analytics team.

Designs, develops, deploys, and supports production AI/ML solutions for healthcare operations. Builds scalable machine learning services, data pipelines, cloud applications, and MLOps workflows; implements CI/CD, monitors and optimizes deployed systems, evaluates emerging AI technologies, and collaborates with product, architecture, data science, and engineering teams. The role also mentors junior engineers and contributes to technical standards, code reviews, and architecture decisions.

Classify patent applications using CPC and USPC systems through technical research, patent classification rules, and automated tools. The role involves developing expertise across emerging technologies, meeting production and quality standards, conducting independent research, and collaborating with a team. Extensive training and mentorship are provided.

Own the strategy, roadmap, and delivery of enterprise IAM data products supporting access governance, privileged access, authentication, authorization, analytics, reporting, and AI-driven identity services. Lead product prioritization, data architecture and governance, dashboards, risk intelligence, regulatory readiness, and cross-functional execution with cybersecurity, engineering, risk, compliance, audit, and business stakeholders.

Leads architecture and technical strategy for large-scale Blue Yonder enterprise transformation programs. Designs and governs integrated solutions across cloud platforms, ERP, automation, robotics, and third-party ecosystems. Establishes integration, API, data, security, scalability, observability, and operational-readiness standards. Advises executive stakeholders, influences product strategy, mentors architects, manages technical risks, and identifies opportunities for AI, machine learning, and intelligent automation.

Leads enterprise workforce management, forecasting, capacity planning, and optimization across service channels and operations processing. Partners with executive leaders to align staffing with demand, growth, productivity, cost, and client experience goals. Uses AI, automation, predictive analytics, and workforce intelligence to improve operational effectiveness. Establishes governance and performance metrics, plans for business events and demand fluctuations, and builds a high-performing workforce planning and analytics organization.

Lead the design, implementation, and scaling of tax-optimized portfolio trading, direct indexing, and overlay solutions. Manage daily tax-efficient workflows, trade execution, account optimization, performance analytics, and scalable UMA capabilities. Partner with advisors, executives, and internal stakeholders; develop training and presentation materials; implement automated trading technology; and oversee risk modeling, tax-aware rebalancing, and process improvements across complex investment portfolios.

Leads rebate financial strategy and drug profitability for a $70B+ portfolio. Oversees financial planning, forecasting, assumptions governance, profitability analytics, scenario modeling, trade capacity modeling, finance transformation, and executive decision support. Partners with senior Finance, Trade, Underwriting, and Operations leaders to optimize margins and profitability, while building high-performing teams and advancing analytics, automation, AI, and technology adoption.

Lead design and execution of AI-enabled workforce management forecasting, capacity planning, and data pipelines for CX. Build governance, dashboards, and predictive models, partner cross-functionally, monitor real-time alerts (PagerDuty), and provide staffing and hiring recommendations to optimize contact center operations.

Nine-week summer analyst program within Operations supporting processing, trade/asset support, reporting, transformation, and data management. Responsibilities include transaction processing, reconciliations, client lifecycle support, data analytics and reporting, risk reporting, process improvement, and creating Tableau dashboards. Program includes training, networking, and may lead to full-time roles.

Lead technical vision and architecture for enterprise ML platforms and MLOps. Design training, feature, serving, and observability systems; establish ML lifecycle and governance; solve complex cross-team engineering problems; mentor senior engineers; evaluate emerging AI technologies; drive cost optimization, compliance, and organizational alignment.

Build AI-powered digital twins that simulate customer behavior and decision-making. Lead data science and AI initiatives involving LLMs, RAG, agentic systems, experimentation, validation, and performance measurement. Apply behavioral science, UX research, and marketing analytics to develop human-centered models. Partner cross-functionally to translate business problems into scalable solutions, communicate recommendations, and mentor junior team members.

Design and deliver enterprise AI solutions using agentic AI, LLMs, NLP, RAG, multi-agent systems, and tool orchestration. Partner with stakeholders to identify high-value use cases, define success metrics, and focus on business outcomes. Build scalable, reliable, explainable, and governed systems with evaluation, monitoring, and guardrails. Advise teams on responsible AI adoption, contribute to strategic best practices, and mentor colleagues.

Supports business decision-making through data analysis, predictive modeling, statistical and machine learning techniques, and presentation of insights. Interns will work across marketing, lending, indirect lending, and warranties while gaining hands-on experience throughout the data science lifecycle. The role is an 11-week, paid, on-site internship based in Tempe, Arizona, or Dallas, Texas, with no relocation assistance.

Design, develop, and productionize machine learning and generative AI solutions; build conversational AI and cloud-based systems; troubleshoot and support production; lead deployments; mentor teams; drive end-to-end delivery and responsible AI practices.

Develops and maintains profitable vehicle transportation lane pricing across automotive customer segments. Responsibilities include benchmarking rates, building pricing models and dashboards, auditing rate and billing data, supporting bids and contract pricing, forecasting margins, identifying revenue leakage, and recommending rate changes. The role partners with Sales, Operations, Finance, Data Science, and Engineering while governing rate structures, documenting methodologies, and improving pricing automation and data quality.

Classify patent applications using CPC and USPC systems, technical research, and automated tools. The role involves learning classification processes, evaluating applications across computer science and electrical engineering technologies, expanding technical expertise, and meeting production and quality standards independently while collaborating with a team.

Performs wafer-level semiconductor device characterization, reliability testing, and automated measurement development. Operates probe stations and parameter analyzers, develops Python-based instrument control and data-analysis workflows, validates data quality, troubleshoots integrated hardware and software systems, and applies statistics, AI, and machine learning to anomaly detection, test optimization, predictive maintenance, and reporting. Owns laboratory test systems, calibration, maintenance, compliance, scheduling, documentation, and user training while collaborating with engineering, facilities, vendors, and external partners.

Design and guide enterprise-scale, cloud-native solutions leveraging software engineering and AI. Provide technical leadership across SDLC, design mobile/cloud apps, integrate via APIs and data services, implement CI/CD and release/configuration practices, and architect end-to-end ML pipelines for cloud and edge deployment while aligning solutions with business objectives.

Lead enterprise AI strategy, governance, and adoption; partner with business and technical leaders to prioritize use cases, measure value and risk, and guide secure, responsible implementation of AI solutions while managing and developing AI talent.

Lead end-to-end analytics for Flagship Client and Distribution: partner with stakeholders to frame problems, perform advanced analyses and machine learning, ensure data quality, develop recurring analytics products and executive visualizations, and mentor analysts to drive data-driven decisions.

Leads technology development for composite wind blade design, materials, manufacturing, tooling, and automation. Owns maturation from early research through production implementation, establishes technology roadmaps and stage-gate processes, and applies AI/ML to engineering and manufacturing challenges. Builds technical teams, manages budgets and partnerships, directs modeling and validation, supports production transitions, develops business cases, and protects intellectual property. The role collaborates globally with engineering, operations, quality, suppliers, customers, universities, and technology partners.