Top Artificial Intelligence Jobs

Lead a team of data scientists to develop AI/ML solutions, leveraging advanced technologies for customer interactions and product innovations. Build and implement NLP models for large-scale applications while collaborating with cross-functional teams.

The Director of AI Customer Success oversees enterprise client relationships, ensuring success metrics and driving AI adoption, retention, and value realization through strategic consulting and collaboration with internal teams.

Lead applied research and engineering for feedback-driven agentic AI: define reward modeling and reinforcement learning roadmap, design production learning loops and evaluation frameworks, run large-scale experiments, and ship research into production while partnering across product and engineering.

The Director of Data & AI Partnerships is responsible for developing account strategies, cultivating partnerships with pharma/biotech clients, and driving revenue goals while ensuring delivery on strategic objectives.

The Conversational AI Operations Specialist will manage and optimize the AI chatbot Sidekick, focusing on quality assurance and content operations.

Join the Inference team to implement features and improvements for model serving on a GPU platform, focusing on performance and reliability.

The Staff Software Engineer will lead the architecture and design for AI workload orchestration on Kubernetes, mentoring engineers and driving technical initiatives across teams.

Lead design, architecture, and deployment of end-to-end ML solutions for onboard autonomous driving. Apply foundation-model alignment, unsupervised pre-training, imitation and reinforcement learning, and scale large-model training pipelines. Collaborate cross-functionally, mentor engineers, conduct research, and productionize foundation models for safe, reliable real-world driving.

Build and deploy scalable ML training and evaluation platforms, drive technical projects and architectural decisions, collaborate with partner teams, prioritize platform improvements, ensure reliability and performance, and mentor junior engineers.

The role involves optimizing large-scale ML infrastructure for autonomous vehicles, conducting analyses, collaborating with teams, and improving system performance.

Lead design and delivery of production-grade AI capabilities to improve developer productivity across engineering tools, CI/CD, and embedded software workflows. Define technical vision, integrate AI into toolchains, drive productionization, establish responsible AI standards, mentor engineers, and influence cross-functional roadmaps and implementations.

Design, implement, and deploy ML models for autonomous driving (detection, tracking, trajectory generation). Apply advanced techniques (imitation learning, RL, foundation models), collaborate cross-functionally, and support production ML systems and model deployment.

The Senior AI Engineer will design and build AI-powered automation tools, maintain LLM systems, and collaborate with business analysts to enhance processes across various operations.

As a Senior AI Engineer, you'll design and implement AI-powered automation tools, maintain LLM-based systems, ensure data quality, and enhance business processes through AI solutions.

As a Senior AI Engineer, you will design and build AI-driven tools and pipelines to automate business processes, ensuring production reliability and integrating AI technologies into operations.

Lead strategy and delivery of AI-powered, agentic product features for a SaaS insurance platform. Define roadmaps, KPIs, ROI, and success criteria; collaborate with engineering and data science to prototype, test, and launch; drive adoption, mentor junior PMs, and align cross-functional teams from discovery through GTM.

The Staff Product Manager will lead AI product strategy and execution, focusing on IT solutions across the enterprise, ensuring compliance and driving adoption.

Build end-to-end agentic AI systems for healthcare customers: discover needs, architect and code solutions, onboard customers, monitor and iterate production systems, mentor junior builders, and collaborate with stakeholders to deliver reliable, AI-native patient workflows.

Lead end-to-end product builds by orchestrating AI coding agents to create applications, automations, and basic agents. Translate customer problems into deployable solutions, instrument usage and outcomes, evaluate AI output for security/privacy/quality, engage with customers to find automation opportunities, and document prompts, patterns, and approaches for the team.

The AI Engagement Manager will lead strategic relationships with institutional owners to harness AI, improve asset performance, and drive measurable ROI across real estate portfolios.

Lead design and delivery of enterprise integrations, automation, and AI-driven workflows across SaaS platforms. Architect scalable APIs, middleware, and conversational self-service; partner with Security, Infrastructure, and Product to reduce operational toil and enable reliable, extensible enterprise platform capabilities.

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.

Develop algorithms, predictive models, quantitative analyses, and visualizations using structured and unstructured data. Apply machine learning, artificial intelligence, natural language processing, statistical programming, and data mining to help clients solve complex problems across public and private sectors. Collaborate with clients to understand needs, uncover insights, and transform disparate data into actionable information. The role requires a Secret clearance and a bachelor’s degree.

Develop predictive models, algorithms, quantitative analyses, and data visualizations from structured and unstructured data. Explore, clean, analyze, and interpret complex datasets using statistical programming, machine learning, NLP, and text-mining techniques. Collaborate with clients to identify data-driven solutions, lead solution development for complex programs, guide teammates, and provide insights supporting informed decisions.

Develop algorithms, predictive models, and data-driven systems using structured and unstructured data. Perform data exploration, cleaning, analysis, visualization, mining, and modeling to answer client questions and support informed decisions. Apply statistical programming, machine learning, artificial intelligence, and natural language processing techniques across public- and private-sector challenges. Collaborate with clients in data-rich environments and translate complex datasets into objective, actionable insights.