Top AI Engineer Jobs

Design, build, and run large-scale backend and data infrastructure; productionize and run experiments on AI/ML models; implement MLOps best practices (versioning, monitoring, alerting); improve model accuracy, speed, and cost; and drive engineering process and culture improvements.

The role involves building and maintaining AI safety systems, collaborating with engineers to improve AI model safety, and managing incidents to enhance user safety.

Develop, design, and maintain AI/ML software solutions; collaborate with engineers and leadership; build tools to analyze large-scale data; debug, profile, optimize, and test software; create documentation and user support materials; leverage modern LLM tools to accelerate development.

Lead research and development of novel ML and deep learning algorithms from data and architecture design through evaluation and transition to production. Prototype research ideas, run benchmarking experiments, build reproducible research tooling, and communicate findings to leadership.

The role involves developing AI strategies, innovating across platforms, mentoring engineers, and participating in product and architectural decision-making.

As a Senior QA Automation Engineer, you will design automation frameworks, test AI features, and collaborate with developers to ensure high code quality.

Design, analyze, and test DC-DC power converters and electrical power subsystems for space-rated satellites. Define requirements, perform verification testing and analysis, and collaborate with multidisciplinary teams to produce reliable, high-efficiency power electronics for orbital AI compute platforms.

Develop AI systems to enhance user experiences, collaborate with cross-functional teams, and mentor AI best practices while growing the team.

Design, analyze, and test DC-DC and other power converters for space; perform system-level power trades and verification; develop requirements; collaborate with multidisciplinary teams to produce robust, high-efficiency power electronics for orbital AI satellites.

The AI Full Stack Engineer will design and build AI-powered healthcare products, oversee backend and frontend development, and influence technical direction in a collaborative, fast-paced environment.

Develop and deploy innovative AI systems to enhance Factory's core capabilities, integrating research findings into practical solutions and addressing scalability challenges.

As a Full Stack Engineer III at Calendly, you'll develop features, scale the platform, and mentor team members while using various technologies.

Design, build, and iterate AI agents, copilots, and assistant experiences using Microsoft Copilot Studio, Azure AI, and Power Platform. Configure knowledge sources, partner with stakeholders to prototype solutions, evaluate agent performance, refine prompts and grounding, and document and package reusable templates toward production readiness.

The role involves designing, developing, and maintaining AI/ML tools, particularly focusing on LLM orchestration frameworks and data optimization, while collaborating with mission stakeholders and supporting security assessments.

As a Senior AI Platform Engineer, you will architect AI-driven systems, develop CI/CD pipelines, and optimize infrastructure for AI workflows.

The Principal Engineer will architect and develop scalable AI-driven data platforms, mentoring engineers and aligning technical strategies with business goals.

Lead the design and development of machine learning solutions, overseeing the entire software development lifecycle and mentoring engineers. Drive innovation in Generative AI and high-performance systems.

Develop and maintain C++ machine control and data analysis software for advanced mask inspection systems. Collaborate with multidisciplinary teams to define system requirements, optimize performance, support integration and testing, and resolve customer escalations. Work in Linux environments and leverage RPC/REST APIs, containerization, and modern UI frameworks as needed.

The role involves designing and developing AI-driven software to improve geospatial data quality. Responsibilities include developing ML components, collaborating with cross-functional teams, and integrating AI algorithms for product releases.

Design, deploy, and operate scalable AI infrastructure for large-scale training and inference. Evaluate emerging hardware/software, integrate GPU/TPU clusters, manage storage/networking and data pipelines, optimize performance and reliability, implement security and compliance, and collaborate with AI researchers and engineering teams to produce repeatable platform standards and reference architectures.

Lead design, development, and production deployment of enterprise AI agents and LLM-powered tooling to automate engineering workflows. Define technical vision, set standards, mentor engineers, partner with stakeholders, and ensure reliability, observability, and scalability of agentic systems.

Operate and support production AI infrastructure across global datacenters, focusing on high-performance NVIDIA GPU platforms, Kubernetes, and high-speed networking. Monitor and troubleshoot infrastructure, network, hardware, and platform incidents; participate in incident response and root cause analysis; improve observability, automation, and operational runbooks.

The Sales Engineer will support account teams, conduct product demonstrations, develop technical proposals, and analyze customer data scenarios to promote data observability solutions.

Develop and prototype AI-driven applications, validate ideas with real data, and transition projects into production while collaborating with teams and customers.

Design and deliver derivatives hedging and financing solutions by building pricing, risk, and scenario models; develop data pipelines and analytics platforms; create AI-driven agentic workflows and knowledge tools; integrate AI with internal systems for real-time analytics; support front-office OTC derivatives, client pitches, and proprietary platform development.