Machine Learning Jobs in Tempe, AZ

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.

Lead design and delivery of servicing readiness and operating models for a new Small Business Insurance segment. Define workflows, roles, inquiry handling, escalation paths, and enablement. Partner cross-functionally to launch, scale, and continuously improve processes using data and AI-informed tooling while managing stakeholders and executive communications.

Develop and deploy predictive and descriptive models (including ML) across the customer lifecycle, perform deep-dive analytics, build BI to monitor program results, and partner with stakeholders to apply risk modeling and analytics to business problems.

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.

Develop and implement supply chain and production planning strategies to optimize inventory, analyze demand and supply, manage suppliers and contracts, lead process improvements, and apply ERP, analytics, and AI to improve efficiency and reduce costs.

Lead identification, assessment, and execution planning for AI/ML, automation, and process improvement initiatives. Perform process mapping, data analysis, SME interviews, KPI definition, and change management. Partner with business, finance, and risk stakeholders, prepare senior-management presentations, and support adoption and governance of scalable solutions.

Develop and optimize predictive models for credit and risk, leveraging advanced machine learning techniques to improve accuracy and decision quality.

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

Lead and build an adversarial research team to track advanced threat actor campaigns, perform malware analysis and adversary emulation, and translate findings into high-fidelity, AI-driven detections. Publish research, represent the company publicly, and collaborate with SOC, IR, and engineering to operationalize intelligence into detection logic and response.

The Vice President of Data Science oversees AI-driven clinical insights and predictive modeling, leading a team to develop novel AI signatures from clinico-genomic data. Responsibilities include strategy execution, model governance, and collaborative efforts across multiple departments to enhance precision medicine.

Senior individual contributor responsible for leading pet/P&C insurance pricing model development (GLMs and ML), owning end-to-end projects, performing EDA and root-cause analysis, communicating results to stakeholders, and mentoring junior team members.

Provide TCAD modeling and EDA tools support for device design and product engineering. Resolve support tickets, review vendor roadmaps, develop EDA enhancements including AI agents and workflow automation, and work across silicon and wide bandgap technologies.

Develop numerical models and experiments to simulate and improve manufacturing processes, support production transitions for new blade programs, implement AI/ML solutions, expand IP, and mentor site engineers while providing production design and troubleshooting support.

Develop, deploy, and maintain quantitative and optimization models for BESS dispatch, renewables, gas generation, and power market analysis. Build CWENQuant platform, data pipelines, and dashboards; create stochastic and ML/DL forecasts; perform mark-to-market, underwriting, and risk analysis; benchmark models and provide analytical insights to trading, origination, development, and asset management.

Lead execution of enterprise pricing strategy and day-to-day pricing operations. Drive pricing tools, optimization platforms, analytics, AI/ML applications, and commercial workflows. Support field sales with proposals, agreements, approvals, and pricing guidance. Manage and develop a team of senior pricing analysts, lead cross-functional initiatives, and deliver measurable pricing and margin improvements.

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.

Seeking a Senior Cybersecurity Analyst for monitoring threats, responding to incidents, and utilizing AI/machine learning tools within SOC. Responsibilities include threat detection, incident analysis, and integration of Google SecOps tools.

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.

Design and implement Dynamics 365 Finance solutions, lead fit/gap and integration architecture, optimize finance processes (GL, AP, AR, cash, fixed assets, project accounting), oversee project delivery, enable reporting and AI-driven automation, mentor functional teams, and advise finance leadership on ERP, Copilot, and data/AI strategy.

Senior analytical leader managing supervisory AI models across their lifecycle, ensuring governance, validation, change management, audit readiness, performance reporting, and pipeline prioritization. Leads and mentors model managers, collaborates with compliance, technology, and operations, and translates technical model concepts for executive and supervisory stakeholders.

Apply statistical and machine learning methods to workforce data to generate insights for talent, retention, and workforce planning. Build predictive models, dashboards, automated reporting, and support HCM implementations while ensuring data governance, privacy, and ethical use of employee data. Partner with HR, Finance, IT, and business leaders to translate analyses into actionable recommendations.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Design, build, and deploy ML models and end-to-end pipelines; implement MLOps practices; deploy containers to cloud production; monitor model performance and drift; collaborate with engineers and product teams; optimize latency and throughput; write production-quality code and mentor junior engineers.

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.