Top Machine Learning Jobs in Tucson, AZ

The VP of Data and AI will define and execute data and AI strategies, lead technical teams, oversee data platform infrastructure, and drive measurable business outcomes.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

The Product Marketing Manager will develop go-to-market strategies, create compelling messaging, perform market research, and collaborate with product and sales teams to position Oscilar's AI risk platform effectively.

Provide legal support for commercialization and product development of an AI-powered ad tech platform: draft and negotiate commercial agreements, manage IP portfolio and complex IP litigation, advise on AI, data, and privacy matters, counsel product teams on compliance and IP protection, and develop automated legal workflows.

Lead Lean transformation initiatives and AI coordination to enhance process excellence across multiple business functions, coaching teams and ensuring integration with operational standards.

Lead enterprise architecture and define future-state cloud, data, and integration platforms. Guide DevOps, data, integration, and infrastructure teams; design scalable secure cloud and on-prem solutions across AWS/Azure/Nutanix; drive IaC, CI/CD, automation, monitoring, cost optimization, and security; advise senior leadership and mentor engineering teams.

Two research fellows will receive a stipend and compute credits to pursue projects in legal AI and automated negotiation. Fellows get expert access, private contract data, and are expected to produce a publishable paper, benchmark, or open-source artifact. Research topics include reward modeling under expert disagreement, negotiation simulation, minimal-diff editing benchmarks, uncertainty/hand-off strategies, or related legal AI problems.

Lead and execute independent research programs on NLP and LLM safety, design and run experiments, secure funding, publish and present results, lead cross-functional teams, and develop evaluation tools and challenges to advance digital safety.

Independently validate and monitor machine learning models for credit underwriting, credit risk, and fraud detection. Identify model weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Support and maintain the Model Risk Management framework and coordinate with Internal Audit, Internal Controls, and Compliance on audit and regulatory requests.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

Design, develop, and implement secure, scalable cloud systems (Azure/AWS); perform system engineering, risk assessments, and NIST-compliant ATO/ATD processes; manage secure data ingestion and orchestration; integrate AI/ML concepts; secure communications and network infrastructure; present technical findings to senior USG leadership and provide hands-on support.

Evaluate and strengthen AI model behavior on cybersecurity topics by writing expert prompts, annotating and grading model responses for accuracy and safety, and applying structured guidelines to classify sensitive content. Work part-time on AI safety tasks with emphasis on secure, responsible handling of dual-use information.

Research, deploy, and maintain AI models and automation solutions; integrate systems and APIs; manage AWS infrastructure and PostgreSQL databases; build BI dashboards; monitor and optimize AI systems and provide technical support.

Design, prototype, and deploy production-ready AI products using ML and generative AI. Lead cross-functional teams, collaborate with stakeholders to solve workflow problems, build scalable prototypes and proofs-of-concept, and apply latest ML/GenAI research techniques.

Own growth and performance for Kits AI across funnel optimization, activation, retention, pricing, and monetization. Productize ML capabilities into creator-facing workflows, partner with research and engineering, run experiments and analytics (e.g., Amplitude), conduct customer research, and leverage AI tools to accelerate shipping and internal insight systems.

Lead end-to-end healthcare fraud investigations for Clover's Medicare Advantage business. Own caseloads, gather and analyze claims and medical evidence, coordinate legal support, prepare defensible referral packages, leverage AI and analytics tools, and collaborate cross-functionally to drive recoveries and provider actions.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

The AVP, Digital Portfolio Management oversees P&L for small business products, driving underwriting profitability and digital transformation through analytics, cross-functional collaboration, and strategic initiatives.

Seeking a Senior Full Stack .NET Developer to work on a social good project, with strong skills in C#, AngularJS, design, and UX. Requires 5+ years of experience.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

The Customer Solutions Manager enriches client relationships by driving data adoption, providing analytics insights, and identifying growth opportunities. Responsibilities include client engagement, data storytelling, and advocating for client needs internally.

Lead the Interventions engineering pillar owning technical strategy and execution for early diagnosis, longitudinal care, and treatment. Scale data and ML infrastructure, improve clinical data accuracy, manage ML/LLM features, drive AI-assisted SDLC, and partner cross-functionally with Product, Data Science, and Clinical Operations to meet clinical performance goals.

Lead manufacturing process improvements for precision optical production: analyze data, reduce cycle time and costs, design/qualify tooling and automation, apply Lean/Six Sigma and AI-enabled analytics, maintain process documentation, partner cross-functionally, drive CAPEX and continuous improvement projects, and train production staff.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.