Machine Learning Engineer

Join ServiceNow's Multimodal team as a Machine Learning Engineer. You will design, build, deploy, and operate services that enhance the platform's understanding of documents, images, and videos. Your work will involve integrating LLMs into production systems, deploying and scaling services on Kubernetes, and ensuring quality and reliability in production. You will collaborate with product managers, engineers, designers, and other teams to define success criteria and communicate capabilities and limitations.

- Design, build, deploy, and operate the services behind ServiceNow's multimodal AI capabilities, helping the platform understand documents, images, and videos. - Build scalable ML services. Design, develop, and improve services and pipelines for document extraction, visual understanding, and agentic automation, integrating LLMs into production systems. - Collaborate across teams. Partner with product managers, engineers, designers, and consuming product teams to define success criteria, understand tradeoffs, and communicate capabilities and limitations clearly.

- Understanding of computer vision techniques and the ability to evaluate model quality independently, including designing test sets and choosing the right metrics - Experience leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry - Projects, research, or work involving document understanding or multimodal models is a strong plus - Experience building, deploying, and operating services, with attention to scalability, observability, and reliability - Master's degree in Computer Science, Machine Learning, or a related technical field, with 1 to 3 years of related experience - Solid understanding of machine learning fundamentals and how LLMs and vision-language models are integrated into applications - Curiosity and a track record of using AI tools to improve engineering workflows - Strong command of software engineering fundamentals, including data structures, algorithms, system design, APIs, concurrency, and testing. Java or JavaScript experience is a bonus - Eagerness to learn, take ownership, and grow in a collaborative team - Hands-on experience with Docker and Kubernetes