Top AI Engineer Jobs

The Lead AI/DevOps Engineer will drive customer experience by leading DevOps initiatives, managing AI infrastructure, and collaborating with teams for innovative AI solutions.

The Lead AI/DevOps Engineer will lead DevOps initiatives, design AI infrastructure, develop solutions for AI use cases, and optimize cloud resources. They will collaborate with customers, security teams, and infrastructure teams to deliver effective AI solutions.

The Lead AI/DevOps Engineer will manage AI infrastructures, lead DevOps initiatives, and develop scalable solutions while collaborating with customer teams and security departments.

Lead AI/DevOps Engineer responsible for driving customer experience through innovative AI solutions, managing scalable infrastructure, and collaborating with various teams to optimize AI workloads.

The Lead AI/DevOps Engineer will design, deploy, and manage AI infrastructure, lead DevOps initiatives, and optimize cloud resources while ensuring compliance with security standards.

Lead the design, development, and implementation of Generative AI applications, ensuring high performance and scalability in cloud-native environments. Collaborate with AI/ML teams to drive innovation and apply best practices in machine learning engineering.

As an Intern at Scout Motors, you'll assist with data management, governance policies, developing ETL/ELT pipelines, and collaborate with cross-functional teams, while gaining hands-on experience in the automotive industry.

As an intern at Scout Motors, you will collaborate with cross-functional teams to enhance data workflows, develop governance policies, and document data management processes. You will gain hands-on experience in the electric vehicle industry while applying analytical and problem-solving skills.

As a Senior Applied AI Engineer, you will build and deploy full-stack AI solutions, mentor engineers, and lead AI system architecture while contributing to Komodo's AI-first culture.

As an Applied AI Engineer, you'll design and deploy end-to-end AI solutions, working with product and data teams to enhance healthcare data usage and AI capabilities.

Join Celonis' 12-month Orbit program to consult with customers, prototype AI and ML/LLM solutions on the Celonis platform using SQL and PQL, run proofs of concept, present value to executives, and collaborate with product, implementation, and partners to realize customer value.

Support AI feature development in secure applications within a federal setting, focusing on generative AI and cloud-based solutions, collaborating in an Agile team.

The Quantitative Researcher (NLP) will use NLP for data feature construction, formulate research hypotheses for alpha generation, build and test trading signals, and launch signals into production.

The AI Engineer designs, develops, and maintains enterprise-level generative AI solutions, leveraging MLOps and cloud technologies while collaborating across architecture teams.

The Senior AI Engineer will develop cloud-based AI products, architect systems for LLMs, and provide technical guidance, while ensuring high standards and performance.

Lead the architecture and deployment of LLM-powered conversational chatbot systems, optimizing performance and ensuring scalability in a crypto environment.

The AI Engineer will design and build production-grade AI systems, translate enterprise challenges into solutions, and collaborate with customers to enhance AI capabilities while managing the technical direction of the AI stack.

The Applied AI Engineer I will implement AI models, build workflows, integrate AI tools into research, and collaborate with ML scientists in a clinical setting.

The Lead AI Developer leads the design and deployment of AI solutions for vehicle systems, integrating full-stack technologies and mentoring junior engineers.

Designs and operates AI Ops pipelines to deploy, monitor, and improve ML models in production. Integrates models with observability, ticketing, and automation systems, defines operational metrics and guardrails, partners with SRE/NOC, and supports incident response and root-cause analysis using AI techniques.

Design and build core systems for data processing and AI pipelines, ensuring reliability and scalability for enterprise clients while mentoring junior engineers.

The Founding AI Engineer will design and implement production-grade AI systems focused on orchestrating complex workflows using LLMs and modern AI tools. Responsibilities include architecting, building, and optimizing systems while collaborating with founders and partners on product development.

The AI Developer role focuses on building AI solutions, automating workflows, managing configurations, and supporting AI operations using Microsoft's AI tools.

Build and operate AI platform infrastructure, integrations, and custom AI-powered applications; evaluate AI providers; enable company-wide AI adoption through training and documentation; ensure deployments meet government security and compliance requirements.

Design, build, and maintain an enterprise AI platform: infrastructure, integrations, and custom AI applications. Own provider evaluation, secure deployments, and company-wide AI training and enablement. Partner with engineering, security, and IT to meet government compliance and operational requirements.