Top AI & Machine Learning Jobs

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.

Develop graduate-level Applied AI course materials, including lessons, labs, case studies, assignments, rubrics, projects, readings, templates, and glossaries. Design practical exercises using LLMs, RAG, AI agents, APIs, automation, and evaluation tools. Collaborate with learning designers and university faculty, revise content based on academic review, advise on Applied AI topics, and maintain current coverage of evolving tools and regulations.

Build and improve ML and LLM systems for CustomerLake personalization use cases, including recommendations, targeting, churn, and lifetime-value modeling. Develop production evaluation and monitoring frameworks tied to business outcomes, inspect model behavior, and advance novel methods. Partner with product, engineering, and design to create scalable solutions, establish ML/AI best practices, and lead ambiguous 0-to-1 initiatives from concept through launch and adoption.

Build production LLM systems and agentic workflows for enterprise process automation. Develop context-learning libraries, autonomous knowledge-management agents, continuous learning loops, evaluation and confidence systems, and scalable AI orchestration. The role combines applied research with production engineering, requiring hypothesis-driven experimentation, reliability improvements, and contributions to AI strategy and product capabilities.

Summer intern supporting Sanofi’s US Advanced Analytics team by developing proof-of-concept machine learning and statistical models for commercial marketing and sales use cases. Responsibilities include predictive modeling, optimization, data visualization, model interpretation, stakeholder collaboration, and presenting actionable insights to leadership. Projects may involve marketing mix modeling, ROI analysis, customer segmentation, patient prediction, next-best action, and driver analyses.