It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. Backed by Greylock and Sequoia.
About the role
The Machine Learning Engineer designs, builds, deploys, and operates the services behind ServiceNow's multimodal AI capabilities, helping the platform understand documents, images, and videos. The Engineer works on the platform services and products that bring LLMs into reliable, scalable enterprise features. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Master's degree in Computer Science, Machine Learning, or a related technical field, with 1 to 3 years of related experience
- Software engineering fundamentals. Strong command of data structures, algorithms, system design, APIs, concurrency, and testing. Java or JavaScript experience is a bonus
- Hands-on experience with Docker and Kubernetes
- ML foundations. Solid understanding of machine learning fundamentals and how LLMs and vision-language models are integrated into applications
- Computer vision and model evaluation. Understanding computer vision techniques and the ability to evaluate model quality independently, including designing test sets and choosing the right metrics
- Production mindset. Experience building, deploying, and operating services, with attention to scalability, observability, and reliability
More about this role
The Multimodal team is transforming how ServiceNow understands multimodal content, including documents, images, and videos, by bringing the latest advances in AI into enterprise workflows. We build and own the platform services and products that power use cases across document extraction, visual understanding, and agentic automation. Our team includes ML engineers and applied researchers who are passionate about turning cutting-edge research into reliable products that deliver real customer impact.
The Machine Learning Engineer designs, builds, deploys, and operates the services behind ServiceNow's multimodal AI capabilities, helping the platform understand documents, images, and videos. The Engineer works on the platform services and products that bring LLMs into reliable, scalable enterprise features. This role needs someone who cares deeply about building production-ready ML services: designing clean APIs and pipelines, deploying and scaling services on Kubernetes, and keeping them fast, observable, and resilient. The Engineer owns the quality and correctness of what ships, whether the code was written by a human or with the help of AI coding agents.
- Build scalable ML...
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