Top AI & Machine Learning Jobs

Build and deploy predictive models for automotive lending, including lender approval and rate predictions. Own data pipelines from dealer systems, CRMs, credit bureaus, and providers into Redshift, maintain lender rules and rate tables, monitor model performance, and develop data-driven product features. Collaborate with sales, customer success, dealerships, and engineering while identifying business problems, prioritizing solutions, and shipping prototypes, analyses, dashboards, and full-stack features using AI-assisted development.

Designs and delivers modern data platforms supporting analytics, machine learning, and generative AI. Builds scalable data lakes, warehouses, pipelines, and cloud-native architectures using automation, Infrastructure as Code, and CI/CD. Collaborates with architects, cloud engineers, and customers to create secure production solutions, mentors junior engineers, and develops reusable data products. Requires strong data engineering and AI/ML experience, programming, SQL, cloud platforms, data warehouses, NoSQL, streaming, and customer-facing technical leadership.

Architects and builds WGU’s conversational AI platform, including retrieval, inference, orchestration, tool calling, security, privacy, guardrails, evaluation, observability, and APIs. Develops scalable production services in Java and Angular on AWS, establishes shared standards and platform capabilities, and provides technical leadership, mentoring, documentation, and production support. Requires extensive software engineering experience and hands-on production experience with LLM applications, RAG, tool calling, and AI evaluation.

Develops data, AI, business intelligence, and workflow automation solutions for federal clients. Responsibilities include analyzing processes and data, gathering requirements, building dashboards and analytical applications, integrating data sources, implementing AI-enabled tools, creating prototypes, testing solutions, documenting implementations, and advising government stakeholders. The role also supports data governance, security, privacy, performance monitoring, and continuous solution improvement.

Leads AI governance solution architecture for strategic enterprise customers. Translates customer requirements, regulations, and market needs into scalable platform capabilities, reference architectures, integrations, governance workflows, and roadmap priorities. Partners with executives, product, engineering, legal, privacy, security, and governance teams to drive responsible AI adoption, risk reduction, compliance readiness, and customer expansion. Facilitates discovery sessions, architecture workshops, technical assessments, and executive reviews while establishing reusable implementation patterns and best practices.

Build and operate Python backend services and AWS infrastructure for autonomous identity operations agents. Responsibilities include durable workflows, enterprise connectors, PostgreSQL and vector retrieval, model API integrations, analytics pipelines, usage reconciliation, deployment automation, observability, tenant isolation, audit controls, and recovery testing. The role owns production reliability and safe integrations with Okta, AWS, ServiceNow, and other enterprise systems.

Sets technical vision for Pinterest’s ML and media infrastructure, leading distributed training, fine-tuning, evaluation, inference, GPU optimization, content ingestion, and signal-processing architectures. Partners with AI/ML, Ads, Content, Shopping, and GenAI teams to productionize reliable, scalable platforms, drive architecture decisions and migrations, improve operational standards, and mentor senior engineers.

Leads scientific data quality for a GMP pharmaceutical QC laboratory. Validates instrument-to-LIMS data flows, maintains statistical control limits and Review by Exception logic, troubleshoots analytical data discrepancies, and builds dashboards and analytics. Applies statistics and machine learning to detect anomalies and monitor performance. Supports ALCOA+ data integrity, investigations, CAPAs, and inspection readiness while partnering with QC, IT, and operations teams.

Analyze complex banking datasets using econometrics, statistical modeling, machine learning, and predictive analytics. Develop models supporting loan and deposit performance analysis, risk management, customer experience, and operational efficiency. Build data pipelines, ensure data quality, create visualizations, communicate recommendations to stakeholders, and collaborate across IT, marketing, and risk teams. Provide mentorship to junior data scientists and analysts.

Leads client and advisor analytics by designing, deploying, and monitoring machine learning, AI, forecasting, predictive modeling, and GenAI solutions. Translates business needs into analytical strategies, manages recommendation engine enhancements, ensures responsible AI and governance compliance, and communicates insights to technical and nontechnical stakeholders. Mentors peers and advances scalable data science practices across the organization.