Top AI Engineer Jobs

The AI Platform Engineer is responsible for building and managing Kubernetes-based AI infrastructure, ensuring security, optimizing performance, and collaborating with teams to enhance platform capabilities.

The job involves designing and implementing AI-driven solutions using ServiceNow, focusing on automating workflows and integrating with LLMs.

Design and implement low-level systems software for distributed GPU training, focusing on fault tolerance, performance, and reliability.

Lead the design, implementation, and scaling of ML infrastructure and production AI systems. Optimize workflows, collaborate with teams, and mentor engineers.

This role requires a Senior UI/Frontend Engineer to build high-performance user interfaces for AI products, collaborating with design and backend teams.

Lead the development of AI products, design scalable systems, advance AI foundations, collaborate with stakeholders, ensure quality practices, and mentor engineers.

Lead and mentor engineering teams in delivering scalable, secure software solutions. Drive innovation and AI integration while maintaining high standards and collaboration across teams.

The role involves developing NLP applications, collaborating with teams to create analytical solutions, and transforming data into business insights while utilizing machine learning techniques.

Lead innovation in data pipelines, develop high-volume services, manage production infrastructure, and ensure quality architecture and code.

The ML/AI Engineer will design hybrid ML systems, focusing on classification, NLP, and optimizing inference pipelines while working closely with founders on technical challenges.

As a Senior Machine Learning Engineer, you will build machine learning models, define processes for AI, and ensure the security of AI systems while collaborating with government sponsors.

The Software Engineer will develop AI-driven automation workflows for the Ansible ecosystem, collaborating with teams to enhance the development process and software quality.

Develop scalable full-stack systems for an AI financial agent, build APIs, manage data pipelines, and collaborate on agent integration.

Lead the AI Compute team, overseeing the Kubernetes-based GPU platform lifecycle, enhancing ML engineering efficiency, security, and developer experience.

The Software Engineer (Back End) develops server-side logic and functionality for the Blueflame AI platform, focusing on database management, API development, security implementation, and performance optimization in collaboration with other teams.

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

Develop AI capabilities using Microsoft tools, integrate AI solutions within enterprise systems, ensure compliance and security, and collaborate with team members for continuous improvement.

Design and build scalable full stack applications integrating AI/LLM workflows and microservices, while leading architectural discussions and collaboration among teams.

The Senior Engineer will innovate and develop AI/ML solutions using Java to enhance customer experiences and exceed expectations.

The Senior Engineer will work on Java and AI/ML projects, driving innovative solutions to enhance customer experiences and operational efficiency.

Collaborate on research projects in generative AI and reinforcement learning, design experiments, create datasets, and contribute to publications.

Design and implement evaluation pipelines for AI models, focusing on user feedback integration and performance optimization in consumer products.

The Senior Full Stack Engineer will develop AI/ML features for ClickHouse Cloud, integrating AI capabilities and building user-friendly interfaces.

The role involves managing training infrastructure, implementing distributed training algorithms, and collaborating with AI researchers on model training.

The role involves modernizing a .NET Azure application, focusing on performance and scalability while integrating AI development tools and mentoring junior developers.