Top Artificial Intelligence Jobs

The Chief Architect will lead the technical direction for Legion's Workforce Management platform, focusing on architecture decisions, AI systems, and scalable software solutions. Responsibilities include hands-on coding, technical leadership, and ensuring systems meet enterprise standards for performance and security.

The Project Support Coordinator will assist in data collection for AI and ML, guide participants, manage equipment, and respond to project updates.

The Technical Project Manager will lead client relationships, manage product roadmaps, translate business needs into tasks, and oversee the software development lifecycle while facilitating Agile ceremonies.

The Go to Market Account Executive at Solva will lead enterprise sales engagements with insurers, guiding clients through the sales process and building relationships with senior stakeholders.

Lead product development at Convex by collaborating with founders and engineers, engaging with customers, and owning product analytics to improve developer experience.

Contribute to cloud-native services and tooling for a GPU cloud platform: work on Kubernetes scheduling, APIs, automation, IaC, CI/CD, testing, code reviews, and cross-functional features.

The Lead Robotics Software Engineer will develop key functionalities of Dapster's robot technology, focusing on motion planning and navigation algorithms.

Design, implement, test and deploy production-grade cloud-native software; contribute to architecture and delivery quality; mentor engineers; own services end-to-end (monitoring, incidents, post-mortems); champion CI/CD and IaC; reduce technical debt and support hiring and onboarding.

Design, build, test, and maintain scalable, responsive front-end applications (React/TypeScript). Collaborate with cross-functional teams to implement AI-integrated UIs, optimize performance, and own frontend lifecycle including unit, integration, and end-to-end testing.

The Computer Vision Engineer will develop and improve sports video models, conduct experiments, and collaborate with data teams to productionize models, focusing on player detection and tracking.