Top AI & Machine Learning Jobs

Conduct applied AI safety research using white-box methods such as activation explainers, steering, attribution, and model-internal interventions. Evaluate methods on realistic, large-scale models and agentic coding tasks, develop practical monitors and interventions, publish findings, propose research directions, and engage with researchers, frontier AI developers, governments, and the broader AI alignment community.

Work with strategic enterprise customers to identify high-value AI opportunities, design and prototype AI-powered procurement solutions, demonstrate business value, and drive implementation, adoption, and measurable outcomes. The role combines customer workshops, solution architecture, stakeholder presentations, automation, and domain expertise across procurement, finance, and supply chain.

Build statistical and machine learning models that improve content discovery, user engagement, and retention. Apply causal inference, experimental design, and A/B testing to measure product impact and validate changes. Collaborate with ML engineers to deploy models, translate analysis into product decisions, and develop features using text, multimodal embeddings, and GenAI. Analyze large-scale data and recommender systems to drive measurable improvements in a consumer product serving millions of users.

Develops and supports enterprise generative AI agents, data integrations, automation, reporting, and analytics solutions. Responsibilities include building AI workflows and retrieval-augmented generation solutions, maintaining data quality and governance, managing metadata and lineage, developing integration pipelines and APIs, troubleshooting operational issues, and creating Power BI dashboards. The role translates business needs into technical solutions and promotes responsible AI practices across student success initiatives.

Build Preql’s core agentic AI workflows for financial data cleaning and transformation. Responsibilities include developing LLM-powered data pipelines, conversational interfaces, audit-ready transformation engines, APIs, financial data integrations, and web-based workflow builders. The role owns the full stack, collaborates directly with enterprise customers, and takes the product from proof of concept to MVP while ensuring data lineage, reproducibility, and compliance.

Develop and deploy AI agents using Gracenote MCP servers, lead technical pre-sales and proofs of concept, architect enterprise integrations, guide customer implementations, and advocate for product improvements. The role requires translating complex AI architectures into business solutions, supporting API integrations, and engaging stakeholders from executives to developers. Travel to customer sites globally may reach 40%.

Evaluates and improves AI-powered customer support agents by analyzing conversation logs, testing prompts, refining knowledge and tools, identifying performance gaps, and recommending model and workflow enhancements. The role partners with Product, Engineering, and Operations leaders, automates recurring support workflows, and helps optimize customer experience, resolution quality, and conversion outcomes.

Design, build, and deploy production-grade agentic AI systems, including autonomous and multi-agent architectures, tool-use orchestration, memory, retrieval, and function-calling workflows. Integrate agents with enterprise tools and databases, implement evaluations, guardrails, observability, fallback paths, and human-in-the-loop controls. Lead technical strategy, client collaboration, prototyping, and product direction for enterprise AI initiatives.

Analyze federal workforce data and position descriptions using statistical modeling, NLP, machine learning, and text analytics. Develop dashboards, visualizations, and reports; map duties and skills to job series and grade levels; validate findings with HR professionals and leadership; and provide recommendations supporting accurate, compliant job classification and reclassification decisions.

Build and ship practical AI-powered tools, dashboards, bots, automations, and workflow integrations using Claude and Gemini APIs. Translate operational problems into scoped solutions, connect AI to business systems, iterate based on user feedback, and document every tool with a runbook. Responsibilities include agent and workflow design, MCP connectors, prompt evaluation, regression testing, API cost management, custom coding, and training internal users.