Top Artificial Intelligence Jobs

Responsible for building and maintaining distributed model management systems for AI inference, implementing scheduling solutions, and collaborating to develop scalable APIs and services.

Lead the planning and execution of GenAI initiatives, manage cross-functional teams, and drive alignment with business strategy to realize AI-driven outcomes.

As a Product Manager, you'll lead the development of payroll solutions, manage product strategy, collaborate across teams, and drive go-to-market initiatives.

As a Senior Software Engineer at Red Hat, you will lead feature development for AI and Cloud solutions, ensuring integration with Nvidia technologies and optimizing code for performance, while also mentoring junior engineers.

Lead the design and implementation of AI solutions by integrating Red Hat software with Nvidia technologies, ensuring optimal performance and security.

Lead sales efforts for AI solutions at Labelbox, developing relationships with top AI labs and Fortune 500 companies, managing the sales cycle and ensuring client satisfaction.

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.

Join our AI Ops & Strategy team to optimize workflows using AI, focusing on product, engineering, and operations, while empowering teams with tools and training.

Lead and manage AI and GenAI-focused product development for analytics platforms, ensuring solutions meet business needs and drive growth.

The AI Cloud Engineer will design and operate AI solutions on AWS, supporting GenAI platform development, engineering robust capabilities, and collaborating across teams to optimize cloud infrastructure and services.

The Strategic AI Customer Success Manager will drive AI adoption for strategic customers, ensuring successful onboarding and ongoing engagement while managing complex relationships.

The Principal Data Science role leads AI/ML strategy and delivery for pharma clients, involving advanced modeling and client engagement to drive business growth.

The role focuses on driving AI adoption, managing customer relationships, and ensuring successful onboarding while collaborating cross-functionally to deliver measurable business impact.

The Strategic AI Customer Success Manager will enhance organizational AI adoption, drive customer success plans, and ensure seamless onboarding and activation for strategic clients, focusing on measurable business impact and deep engagement.

Drive AI adoption for strategic customers, ensuring successful onboarding and activation. Guide organizations through deployment, focusing on relationships, activation frameworks, and measurable impacts. Collaborate cross-functionally with teams to enhance customer journeys and build advocate networks.

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

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

The AI Software Engineer will design, deploy, and optimize LLM-powered systems, integrating AI solutions with hardware engineering teams to improve operational efficiency, using Python and cloud technologies.

The Lead AI Researcher will develop new AI capabilities, lead a small team, and transform research problems into practical systems to automate legal processes.

The AI Engineer role involves optimizing language models for fraud detection and building backend infrastructure to support scalable operations for risk management and as well as developing efficient machine learning solutions.

The Applied ML Engineer at Ideogram will turn generative models into production features, collaborate with teams to define metrics, and ensure ML systems' reliability.

Develop and integrate AI solutions for government customers, focusing on machine learning and deep learning technologies. Collaborate with teams and mentor juniors while providing technical reports.

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.

The engineer will improve the reliability and scalability of AI systems, refactor code, resolve distributed system issues, and work with ML researchers.

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