Top AI & Machine Learning Jobs

Lead execution of Responsible Use of AI (RUAI) approvals and AI risk oversight. Coordinate cross-functional reviews, assess and document AI risks, improve governance tools/workflows, and escalate material issues to leadership. Engage use case owners, vendors, and control partners to ensure compliance with AI regulatory and control frameworks.

Design and implement scalable, production-grade AI/ML solutions on an enterprise AI platform. Collaborate with product, architecture, and platform teams to translate requirements, provide design guidance and reviews, ensure reliability/observability and responsible AI compliance, mentor junior engineers, and drive platform improvements and adoption.

Lead design and governance of AI-enabled development platforms and agent frameworks for citizen and associate developers. Define reference architectures, reusable patterns, guardrails, and embedded controls for security, compliance, explainability, and resiliency. Partner with engineering, security, and platform teams to validate solutions, drive adoption, and enable reuse through templates, components, and training.

Analyze government affairs business processes, design and implement AI-powered solutions and workflow automations using Microsoft tools, partner with stakeholders to solve problems, and drive user adoption through training and hands-on support.

Early-career engineer focused on developing and integrating Python components for AI use cases. Support data preparation, model integration, RAG pipelines, embeddings, and vector retrieval. Collaborate with senior engineers on testing, debugging, documentation, deployment, and apply cloud and software engineering best practices under mentorship.

Design, implement, and deploy production-ready AI/ML use cases using an enterprise AI platform and Azure AI services. Collaborate with product, architecture, and platform teams to build microservice-based solutions (LLMs, RAG, vector search). Ensure reliability, observability, and responsible AI standards; contribute to code, testing, documentation, and mentor junior engineers.

Lead Data Scientist responsible for developing and implementing AI and ML solutions to support marketing and business engagement. The role involves technical leadership, model development, data analysis, stakeholder collaboration, and ensuring compliance with governance standards.

Lead product strategy, operating model, and portfolio execution for Composite AI capabilities. Align roadmaps, define technical requirements, embed Responsible AI and governance, coordinate across Architecture, Data & Analytics, and LOBs, and drive adoption, metrics, and product management maturity across a federated model.

Design and implement production-ready AI/ML use cases on an enterprise AI platform. Collaborate with product, architecture, and platform teams to translate requirements, develop code/configuration, test, and deploy solutions. Ensure quality, reliability, observability, and responsible AI compliance. Contribute to solution design, troubleshoot performance issues, and participate in code reviews and documentation while mentoring junior engineers.

Senior individual-contributor role to design, build, and operationalize security controls for enterprise AI systems. Responsibilities include hardening AI hosting environments (cloud-native, Kubernetes), protecting prompts and sensitive data, improving detection/telemetry for model misuse, integrating controls into CI/CD and ML lifecycles, evaluating AI security tooling, and enabling cross-functional teams with secure implementation patterns and guidance.