Top AI Engineer Jobs

The Senior Backend Engineer will lead AI-focused projects, optimize data pipelines, mentor juniors, and enhance customer support through innovative technologies.

Seek an AI-Driven UI/UX Developer to design and implement user interfaces in code, collaborating with AI tools, while ensuring performance and quality.

Develop and maintain AI systems, collaborate with teams, debug production issues, and mentor engineers to ensure high-quality AI features.

Lead development and deployment of real-time, on-device computer vision models for outdoor home monitoring. Architect, train, and optimize transformer/CNN-hybrid models for embedded cameras, ensuring accuracy, latency, memory, and power budgets. Collaborate with firmware and platform teams, define evaluation strategies, perform failure analysis, improve long-tail robustness, and mentor engineers while setting technical direction and best practices for reproducible edge ML workflows.

As a Staff Machine Learning Engineer, you will develop models and agents for AI integration into products, focusing on performance monitoring and issue resolution.

The Sr. Software Engineer will lead AI product development, integrate AI solutions across workflows, and mentor team members while ensuring system scalability and resilience.

The Research Engineer will develop AI algorithms for autonomous systems, collaborating with teams on end-to-end solutions and data-driven models.

The role involves delivering features across the CRM platform for distributors, using AI tools, handling fullstack development tasks, and collaborating closely with teams and customers.

The role involves developing AI and machine learning solutions to improve organizational efficiency, ensuring user-focused system modernization and compliance with cybersecurity standards.

Design and implement end-to-end AI/ML software solutions to modernize client systems. Build developer-focused tools and prototypes, apply best practices for software workflows, and collaborate to refine experimental tooling while considering ecosystem and future enhancements.

Design, build, and operate large-scale production systems and integrate diverse technologies. Develop AI/ML-enabled end-to-end solutions on AWS, manage Kubernetes deployments, and implement observability. Lead technical initiatives, support policy/governance, and work within TS/SCI polygraph security requirements.

Design, build, and maintain AI assistants and automation workflows across HR, Finance, and Operations. Develop agentic AI, RAG, and integrations using APIs, middleware, and automation platforms. Ensure secure, scalable deployments, measure ROI, document solutions, and train teams on AI-assisted workflows.

The Principal AI Infrastructure Engineer will architect and lead AI infrastructure initiatives, enhance developer experience, mentor teams, and establish standards across ADI's diverse environments.

The AI Software Developer will collaborate with teams to create AI-driven applications, manage product deliverables, and stay updated on AI technologies while solving complex, real-world problems.

The Senior AI Infrastructure Engineer will design scalable AI infrastructure and solutions across diverse deployment environments, collaborating with data science teams to enhance AI development efficiency and governance.

The AI Marketing Ops Consultant builds AI-powered marketing automation and workflows, integrates tools, documents processes, and collaborates with teams to optimize marketing operations.

As an AI Automation Engineer, you'll build custom AI agents, implement integrations, ensure data governance, and contribute to overall AI solutions, collaborating with cross-functional teams.

Design and develop core platform features for synthetic data generation, LLM operations, and agentic workflows. Oversee API design and scalable compute services, enhancing AI model performance for enterprise clients.

Lead development of an internal AI platform and orchestration components to deploy Agents and RAG pipelines. Build core infrastructure, SDKs, APIs, and data pipelines; collaborate with applied scientists, data engineers, SRE, and QE; design developer-facing interfaces; ensure operational excellence, observability, and testable, production-grade AI services.

As a Lead Software Engineer at Thomson Reuters, you will innovate AI-driven software, build backend services, and lead cross-functional teams to enhance accounting workflows through automation and intelligence.

As a Lead Software Engineer, you will design AI-driven backend systems for accounting, integrating LLMs, ensuring performance and security, and collaborating with teams on AI solutions.

The Senior .Net Developer will enhance SDG's C#/.NET Core codebase, design high-load services, and optimize MS SQL queries, benefiting from a remote work environment and attractive benefits.

The Principal Machine Learning Engineer leads the deployment of multi-modal AI models on mobile platforms, setting technical vision and optimizing inference performance, while mentoring a team and collaborating cross-functionally.

Operate and scale an Azure-based AI platform (Companion) by maintaining AKS infrastructure, improving observability, handling incidents, ensuring security and operational hygiene, and building runbooks and processes to support production AI agent workloads and deployments.

Design, build, and operate cloud backend services powering connected hardware: device connectivity, telemetry ingest, state management, and data pipelines. Own features end-to-end, lead medium projects, mentor juniors, collaborate with firmware/mobile/platform teams, apply AI-native engineering practices, and participate in on-call incident response and post-mortems to ensure scalable, secure, reliable systems.