Top AI Engineer Jobs

Lead the transition from teleoperation to autonomy in robots by developing Vision-Language-Action models and deploying ML systems. Collaborate on data processing and model integration for robotics applications.

As a Senior Hardware Systems Engineer, you will lead AI rack and cluster infrastructure designs, manage deployments, and collaborate with cross-functional teams to optimize data center solutions.

Design and develop large-scale AI systems for healthcare, focusing on ML infrastructure, real-time analytics, and collaboration with teams. Requires extensive experience in software engineering and AI.

Design and operate Kubernetes-based platforms for AI/ML systems, manage containerized environments, and develop CI/CD pipelines for secure deployment in mission-critical settings.

The AI DevOps Engineer will design, deploy, and manage scalable AI infrastructure, focusing on automation, security, and high performance while ensuring compliance within financial services.

Lead the design and development of AI solutions and MCP servers, focusing on AWS infrastructure and Python development. Responsibilities include automating processes, managing deployments, and conducting architectural governance.

The AI/Machine Learning Engineer will design, develop, and deploy AI models for healthcare, collaborating with teams to enhance patient outcomes using advanced data analytics and machine learning techniques.

Own and operate Baseten's internal AI stack, build and deploy custom AI agents and LLM-powered tools, evaluate third-party AI developer tools, instrument usage and measure impact on engineering productivity, and support engineering teams in adopting AI workflows.

Lead full-stack development and architecture across frontend, backend, and AI systems. Build scalable services, integrate models and data pipelines, collaborate with product/design, mentor engineers, and deliver high-impact features from design through production.

Build AI-powered features for managing engineering requirements, integrate language models, and maintain infrastructure while collaborating with product teams.

Seeking an AI-Powered Developer for full stack development using AI tools. Responsibilities include coding, problem-solving, and collaborating effectively in a remote environment.

The role involves developing AI-driven cybersecurity solutions, designing ML models for threat detection, and enhancing security frameworks. Candidates collaborate with SOC teams and assess AI system security.

Design next-gen semiconductors for AI/ML applications, leading advanced development processes and optimizing hardware-software integration.

As a Senior AI/ML Software Engineer, you will design and deploy AI systems within a .NET environment, influence technical direction, and mentor engineers while integrating modern AI techniques.

As an AI Research Engineer, you'll design and maintain data pipelines, train models, and work with researchers on innovative solutions.

The AI Platform Engineer will design and implement MLOps pipelines, develop automated CI/CD systems, and optimize ML infrastructure for performance, cost, and reliability.

Lead full-stack development for an AI-native insurance product, owning features from concept to production. Build frontend and backend systems, integrate and orchestrate LLMs and ML models, improve internal developer tooling and CI/CD, collaborate with brokers and customer teams to iterate on AI-driven workflows, and scale the platform across carriers and lines of business.

The Staff Software Engineer will lead the architecture and development of backend services, integrate AI solutions, and enhance cloud-native capabilities while mentoring other engineers.

Seeking an AI Research Engineer to design AI training protocols, build scalable systems, and collaborate on novel AI infrastructure solutions.

As a Business Process Automation Engineer, you'll design low-code solutions using Microsoft Power Platform and AWS tools, enhance workflows with AI, debug technical issues, and collaborate with stakeholders.

Responsible for the full lifecycle of AI/machine learning on resource-constrained hardware, including data ingestion, model development, and deployment on embedded devices, while working closely with cross-functional teams.

The Gen AI Data Engineer II develops and maintains solutions for Generative AI initiatives, including data processing and integration with data scientists and engineers.

The Engineer III - AI designs intelligent systems, leads AI reliability efforts, collaborates on performance metrics, mentors engineers, and focuses on effective communication to solve complex issues.

Design, build, and deploy scalable generative AI systems to improve content metadata and personalization. Lead architecture, MLOps, RAG, prompt engineering, and evaluation; collaborate cross-functionally, integrate ethical AI practices, and monitor performance.

Lead AI-augmented full-stack development from concept to production: define architecture and design-system standards, integrate Figma with AI tools, oversee backend (Supabase, SQL/NoSQL) and auth (OAuth/JWT), manage Jira workflows, mentor engineers, and collaborate cross-functionally to deliver scalable, enterprise-grade applications.