Top AI Engineer Jobs

The Frontend Engineer will lead the development of a web application, focusing on architecture, feature development, and testing, while collaborating with other teams and optimizing performance.

Lead the CRM AI team to drive technical direction and execute the roadmap for an AI-powered CRM platform, focusing on architecture, operational excellence, and cross-functional collaboration.

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.

As a Senior Software Engineer, focus on backend development and AI integration for scientific applications, building systems that leverage advanced AI techniques.

Profile, benchmark, and optimize large-scale LLM training and inference across GPUs, CPUs, HCAs, and switches. Focus on collective communication and high-performance networking, build PyTorch trace-based profiling and replay tools, define performance test plans, and collaborate across hardware and software teams to identify bottlenecks and achieve performance targets.

As a Principal Software Engineer, you will lead AI networking system transformations, manage complex customer engagements, and influence NVIDIA's networking technologies.

Create developer-focused technical content, demos, reference examples, deployment guides, and docs-as-code workflows to accelerate adoption of NVIDIA enterprise AI software. Work across engineering, product, field, and partners to design developer journeys, build sample applications and notebooks, enable sales and partners, capture feedback, and engage the open source and cloud-native communities.

Lead developer marketing programs to acquire, activate, and grow developers building AI applications on PC using NVIDIA SDKs and RTX. Create technical content, run community and partner activations, educate developers on platform capabilities, drive engagement and evangelism across channels, and use analytics to improve program performance.

The Senior AI Software Engineer will design scalable services for AI-driven applications, develop APIs, optimize data pipelines, and ensure system reliability, collaborating with cross-functional teams on edge and cloud AI integration.

The role involves designing and developing scalable services for AI workloads, integrating AI with edge devices, and implementing security best practices. A strong background in backend development and LLM integration is essential.

Design, build, and maintain LLM integrations and AI features; own end-to-end delivery from requirements to production monitoring; ensure scalability, reliability, observability; leverage AI agents to improve developer and operational efficiency; collaborate cross-functionally.

The AI Software Engineer will deploy models, build data pipelines, optimize performance for AI models, and develop testing suites in collaboration with AI scientists.

Design and prototype algorithms for machine learning and reinforcement learning in robotics, focusing on practical problem-solving and real-world application.

The Senior AI/ML Software Developer will design, develop, and maintain AI applications, collaborating with teams and solving complex problems.

Design, build, and maintain secure on‑prem and cloud infrastructure and CI/CD pipelines for Kubernetes-based services. Automate deployments, manage production/staging/dev environments, monitor logs and system health, enforce security controls, and support accreditation (A&A) and operational readiness. Troubleshoot incidents, perform root cause analysis, maintain documentation, and collaborate with Agile teams to drive DevSecOps best practices.

Design, deploy, and sustain AI analytics stack components: build AI-enabled web frontends and APIs, integrate LLM capabilities (prompting, tool-calling, RAG), implement CI/CD and containerized deployments, work with relational databases, and ensure secure, maintainable production software.

Own product areas end-to-end: discover, prototype, ship, and iterate. Build secure, well-tested, observable full‑stack systems; partner with product, design, data, and clinical teams; use data and experimentation to validate impact; improve AI‑native development practices and engineering systems while balancing speed, safety, and reliability in a regulated healthcare context.

The role involves developing and deploying large language models for healthcare, applying advanced ML techniques, and collaborating with interdisciplinary teams.

The IT AI Innovation Engineer designs and maintains AI-driven software systems to enhance legal practice efficiency and operations, collaborating with various teams and ensuring compliance with development practices.

The Principal Software Engineer leads the architectural design of a data platform, ensuring isolated and compliant data flows, overseeing AI data lakes, batch and streaming pipelines, and developing service APIs.

This role involves designing and exporting AI frameworks, enhancing product capabilities, collaborating with teams, and directly engaging with customers.

Design, build, and operate a production generative/agentic AI platform for autonomous SOC workflows. Lead end-to-end feature development, multi-agent pipeline engineering, observability, security, and incident response in federal environments.

The Senior Generative AI Engineer will design and deploy AI/ML solutions, focusing on Generative AI systems and their operational excellence across various sectors like R&D and Clinical Trials.

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.