Top AI Engineer Jobs

As a Senior Staff AI Data Infrastructure Engineer, you will design scalable data pipelines, optimize training throughput, and support infrastructure evolution for AI data management.

Lead the architecture and delivery of AI-powered fraud detection solutions, integrating Generative AI and ensuring compliance while mentoring engineers.

The AI/ML Engineer will develop matchmaking and recommendation systems, scaling them for millions of users while leading a small technical team.

The Senior Engineer role involves full-stack development, integrating AI services, and optimizing workflows with AI tools to enhance UX and testing.

The Lead Engineer will manage AI-enabled internal product development, focusing on full-stack system ownership, agentic coding, and collaboration with cross-functional teams.

The Staff Software Engineer will lead the development of AI-native products by defining architecture, managing deliveries, mentoring engineers, and ensuring product quality in a startup environment.

As a Software Engineer, you will work on AI systems to enhance insurance pricing by analyzing problems, building evaluations, and shipping improvements, focusing on agent systems and production engineering.

The AI Engineer will develop, deploy, and optimize AI solutions using Google's Gemini, working with machine learning models and data pipelines in a client-focused environment.

As a Founding Engineer, you'll manage the lifecycle of AI systems, optimizing performance and developing pipelines for biopharma marketing.

As a Founding AI Design Engineer, you will design visual assets and collaborate with engineers to create a platform that integrates AI with design workflows in pharma marketing.

The Staff AI/ML Engineer will design, build, and improve AI systems for document retrieval and data extraction, work with clients, and mentor team members to establish best practices.

The AI Engineer will develop and optimize AI models and high-performance software systems for drug discovery, collaborating with researchers and maintaining infrastructure.

Join Uplane as a founding AI engineer to develop scalable AI systems. Responsibilities include building AI models, managing databases, and ensuring product alignment with user needs.

Lead architecture and evolution of AI-powered systems, ensuring they are reliable and scalable. Oversee delivery of AI-native systems and establish standards for API contracts and evaluation frameworks.

Design and implement AI-powered solutions for document extraction and financial reasoning, focusing on ML pipelines and application of LLMs.

The Forward Deploy Engineer collaborates with sales to design and implement proofs of concept (POC) for enterprise clients, focusing on integration and workflow optimization while providing product feedback to improve offerings.

As a Software Engineer II, you will design, develop, and maintain AI-driven mobile features, collaborating across teams to enhance mobile experiences used by millions.

Build and improve AI/ML systems and data pipelines for a B2B SaaS platform; shape product and technical strategy; work with customers; mentor team members; ensure secure, robust, and scalable infrastructure.

The Full Stack AI Engineer will design and maintain AI applications, develop backend services, collaborate with data scientists, conduct code reviews, and advise on AI technologies. The role requires extensive Python experience and the ability to obtain a DHS Public Trust clearance.

The Integration Engineer will build enterprise integrations for AI platforms with Microsoft Graph, focusing on API integration, security, and performance optimization.

The Integration Engineer develops enterprise integrations for AI systems using Microsoft Graph API, ensuring secure authentication and data flows while collaborating with senior engineers for production code implementation.

As Lead Edge AI Engineer, you'll architect edge-AI pipelines, build developer-friendly APIs, optimize performance, and mentor engineers while collaborating on decentralized AI solutions.

Lead the development of AI-driven workflows by building data pipelines, deploying ML models, and collaborating with cross-functional teams. Mentor junior engineers and contribute to engineering best practices.