Top Artificial Intelligence Jobs

The Ontology Engineer will design and implement semantic models for a new data platform, ensuring data interoperability and collaboration with AI teams.

Design, build, and deploy machine learning and generative AI systems, transforming prototypes into production systems while collaborating with technical teams.

Lead the design and delivery of AI-powered features as a Staff Software Engineer, focusing on backend architecture, LLM integration, and mentoring engineers.

The Senior AI Engineer will develop AI-driven product features, build scalable systems, apply AI innovations, and enhance user experiences through data solutions while collaborating with cross-functional teams.

The AI Engineer will develop AI/ML solutions for Fortune 500 clients, ensuring integration and optimization, while collaborating with various stakeholders.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

Encord seeks an Account Executive for their Physical AI business to drive sales, manage customer relationships, and collaborate with internal teams.

Develop and teach an AI Leadership course for professionals, creating engaging video content and optimizing learner engagement across diverse fields.

Build and evaluate AI agents and ML models for medical billing, collaborating with operations and customers to improve outcomes.

The AI Integration Engineer will connect healthcare data systems with AI platforms, focusing on data transformations using Python and interoperability standards like HL7 and FHIR, while coordinating with offshore teams and improving integration performance.

The Principal Software Engineer will lead the design and implementation of Docker AI Cloud's distributed systems, focusing on scalable, reliable infrastructure while mentoring engineers and aligning technical strategy with business objectives.

The role involves implementing AI safety strategies, building evaluation frameworks, and developing safeguards against scientific risks from AI models. Candidates must possess strong technical knowledge and communicate complex concepts effectively.

As an AI Engineer, you will develop and optimize AI systems, focusing on LLM integration, vector databases, and RAG pipelines, collaborating with various teams to ensure cutting-edge performance.

The role involves developing new user-facing features for LangSmith, optimizing components, and collaborating with developers and designers to enhance usability.

As an AI Platform Backend Engineer, you'll design and deploy backend systems utilizing AI for real-world applications, optimize performance, and mentor junior engineers while working directly with clients to address complex challenges.

As an AI Platform Engineer, you will design and develop AI-driven backend solutions, optimize performance, and collaborate with customers and teams.

Lead the technical architecture and implementation for LangSmith, collaborating with teams, mentoring juniors, and ensuring code quality.

Manage post-sale customer lifecycle focusing on onboarding, renewals, and revenue growth. Collaborate with clients and teams to drive insights and success.

Pioneering machine learning solutions for the defense sector, developing and deploying production-grade ML models, tackling complex data challenges, and collaborating with engineers.

The AI Engineer will develop AI applications, lead customer engagements, monitor system performance, and provide feedback to influence product direction. Requires expertise in machine learning and software engineering.

The AI Engineer will develop and maintain AI pipelines, design robust models, analyze performance, collaborate with Domain Engineers, and communicate technical concepts to stakeholders.

Design, develop, and maintain full stack applications, integrate AI/ML models, and ensure code quality and performance.

Lead the design and build of automation infrastructure for GTM, enhancing sales and marketing efforts through advanced engineering solutions.

The Marketing Ops AI Manager designs and optimizes AI systems to enhance marketing operations efficiency, data quality, and campaign performance. Responsibilities include developing AI strategies, managing workflows, and training teams on AI applications.

Lead the Organizational Productivity practice, focusing on diagnosing challenges and defining AI- and automation-driven solutions for process improvement across business functions.