Top AI Engineer Jobs

Develop robust AI/ML solutions for manufacturing, collaborating with scientists to build scalable infrastructure, optimizing ML systems, and ensuring code quality.

The AI Engineer will improve text-to-SQL accuracy, build evaluation frameworks, and develop production-grade LLM applications, collaborating with engineering and customers for enhancements.

As an Applied AI Engineer, you will implement AI capabilities into software products, collaborating with teams to enhance developer experience through LLM features and integrations.

The AI Engineer will drive innovation in AI projects at Zoom, focusing on model optimization, software development, integration, and improving AI capabilities across products.

Lead platform engineering in AI developer tools, architecting solutions with AI, automation, and intelligent agents, mentoring teams, and ensuring operational excellence.

The Lead Microsoft365 AI Engineer designs and oversees AI solutions within Microsoft 365 and Azure, ensuring they are secure, scalable, and impactful. Responsibilities include developing AI solutions, leading teams, and setting engineering standards.

As a Senior Robotics AI Engineer, you will develop and deploy AI solutions for robot perception and navigation, ensuring system optimization and robust performance. Responsibilities include managing ML models and collaborating with cross-functional teams.

The Senior Agentic AI Developer will build LLM-based autonomous agents and orchestration systems for fundraising, optimizing donor engagement through advanced reasoning and planning capabilities while ensuring enterprise-grade performance in a collaborative environment.

The Senior AI Engineer will design AI-driven agents for game development, enhancing workflows and capabilities through AI integration across disciplines.

As an Applied AI Engineer, you'll improve Rive's AI capabilities for design and development, integrating AI models while collaborating with the editor team.

Design and implement AI solutions using large language models. Develop AI agents, RAG systems, and text-to-SQL applications while collaborating in Agile teams.

Design, develop, and implement full stack custom software solutions, ensuring product quality through testing and contributing to team success.

Design and implement cutting-edge machine learning models, optimize them for performance on Apple devices, and collaborate with engineers to enhance user interfaces.

The role involves building and scaling Unstructured AI systems, handling large volumes of data, integrating with enterprise sources, and ensuring high-quality AI features.

Design and implement AI-driven tools to improve workflows across teams. Collaborate to identify internal problems AI can solve, and prototype solutions quickly.

Design, implement and optimize AI solutions, manage data pipelines, troubleshoot AI applications, and advise stakeholders on AI strategy in a technical leadership role.

Lead AI Engineer responsible for guiding AI engineering teams, overseeing solution design, ensuring code quality, and mentoring AI engineers.

The Senior AI/ML Applications Engineer will develop, integrate, and support AI-driven tools for IC design and verification, focusing on agentic AI methods to enhance productivity.

The Senior AI Engineer will develop core AI systems for healthcare, focusing on real-time inference and NLP pipelines, ensuring safety and scalability in medical consultations.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

Architect AI Agents to detect and stop adversarial AI attacks. Work in fast-paced environments with evolving models and threats.

The AI Engineer will architect AI agents to detect and counter adversarial AI threats, adapting rapidly to an evolving landscape in cybersecurity.

As an Applied AI Engineer, you will build AI features, customize models, ensure production quality, and collaborate with teams to enhance legal services using AI.

The role involves developing LLM-powered AI features, optimizing AI performance, and collaborating on technical architecture and user experience enhancements. Requires strong skills in machine learning and AI integration.

Develop production-grade AI agents for enterprise customers. Design and build LLM-powered systems, integrating workflows, evaluation, and performance standards. Collaborate closely with customers and teams to ensure reliability and effectiveness in real-world applications.