Top AI Engineer Jobs

The Sr AI Engineer designs and develops AI solutions to optimize business operations, integrating machine learning capabilities to enhance decision making and automation across functions such as supply chain and finance.

Lead design, build, and operation of production AI systems and inference stacks (vLLM) across AI Factory platforms. Implement RAG, MLOps, storage/networking, Kubernetes/containers, monitoring, security, and on-call incident response. Mentor engineers, engage clients, author runbooks, and contribute reusable patterns and tooling.

Responsible for designing and delivering multi-agent systems for AI products, collaborating with data scientists and offshore teams, and writing production-grade Python code.

The AI Engineer will develop AI tooling to enhance internal processes, collaborate on automation opportunities, and maintain AI systems to improve productivity.

The Lead AI Engineer will develop AI and ML systems with a focus on intelligent decision-making and data pipelines to improve agent performance and continuous learning.

The AI Engineer will develop scalable AI systems, automate workflows, and collaborate with business teams to enhance operational efficiency across OpenSesame.

As a Senior AI Engineer, you will design and implement AI solutions, collaborate with teams to define success metrics, and iterate on AI model performance.

The AI Engineer will design, develop, and deploy AI-powered systems, improve operations with intelligent workflows, and collaborate on high-leverage AI opportunities.

As an AI Engineer, you'll lead backend implementation, build AI-powered products, and ensure high-quality systems, contributing to Elicit’s tech stack and user experience.

The Applied AI Engineer will architect, implement, and maintain AI agents for Edison's platform, collaborating with science and engineering teams and gathering insights from R&D partners to improve the agents' capabilities and reliability.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

Lead end-to-end ML implementations for clients, design and maintain production-grade MLOps pipelines, deploy and optimize Generative AI/LLM and NLP solutions, manage infrastructure (Docker, orchestration, distributed compute), and communicate technical results to stakeholders.

As a Forward Deployed AI Engineer, you will integrate Latent Labs' AI models with pharmaceutical clients' workflows, focusing on tech deployment, customer advocacy, and collaborative feedback for product improvement.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Design, develop, and maintain secure MCP Servers for AI integration, ensuring scalability and system security while managing API integrations and tools for AI assistants.

The Senior Technical Data Product Manager will oversee the data product roadmap, collaborating with data engineering and architecture teams. Responsibilities include assessing legacy systems, developing product roadmaps, driving cross-functional deliveries, and ensuring technical requirements are met, aiming for swift execution and measurable impact.

As a Senior AI Engineer, you'll develop and deploy innovative AI solutions for the fashion industry, collaborate with cross-functional teams, and refine machine learning models to enhance product offerings.

Design, train, test, deploy, and maintain AI/ML models and agentic workflows. Build secure cloud data foundations, implement MLOps/DevSecOps, design event-driven integrations, and collaborate with engineers, data scientists, and product owners to deliver mission-critical AI solutions for the Air Force.

The Senior AI Developer Relations Engineer will engage with the developer community, create high-quality content about You.com's search APIs, and grow audience awareness through various interactions and collaborations.

As an AI/ML Engineer, you will develop and optimize AI solutions for renewable energy assets, collaborating with a skilled team to deploy algorithms in real-world projects.

As a Machine Learning Engineer, you will build agentic systems for autonomous web navigation and complex task completion, integrating LLMs and reinforcing learning.

Embed with discovery teams to translate scientific workflows into production AI systems. Rapidly prototype and deploy LLM/RAG-based solutions for multi-omics problems, run evaluation loops, ensure data provenance and reliability, and distill learnings into reusable platform components to drive adoption across therapeutic areas.

Lead design, development, and deployment of production-grade AI systems for mission-critical cyber and intelligence operations. Architect scalable MLOps pipelines, deploy models to cloud, on‑prem, and edge, integrate AI into cybersecurity workflows, ensure secure and RMF-compliant deployments, mentor engineers, and transition prototypes into operational systems.

Develop tactical insights from large structured and unstructured datasets, build and validate ML models and AI tools, design scalable resilient distributed systems, collaborate with analytics and data teams, communicate results to technical and executive stakeholders, and influence departmental strategy while independently driving technical approaches.

Design, architect, and scale cloud backend infrastructure for real-time media and sensor data streaming. Own reliability and throughput SLAs, collaborate with AI teams, and mentor engineers.