Senior Machine Learning Engineer, Agentic Systems - Moveworks
About The Position
Moveworks is an Agentic AI Assistant platform that empowers the entire workforce by enabling employees to converse with all business systems through natural language to find answers and automate tasks. The platform is powered by advanced LLMs, proprietary models, and a sophisticated Agentic AI platform, transforming how work gets done by allowing AI to take initiative, streamline complex workflows, and continuously learn and adapt. Moveworks is trusted by over 5.5 million employees at more than 350 of the world’s largest companies, including 10% of the Fortune 500. Recognized on the Forbes Cloud 100 and AI 50 lists, Moveworks was also named one of Fast Company’s 2025 Most Innovative Companies and Inc’s Best in Business, in the Best in Innovation category. Moveworks was also recognized at Microsoft’s 2025 Partner of the Year and in 2024, received the AI Breakthrough Award. In December 2025, Moveworks was acquired by ServiceNow, combining ServiceNow’s leading workflow automation with Moveworks’ Reasoning Engine and natural language capabilities to deliver an AI platform for every person and every workflow. ServiceNow, founded in 2004, is a global market leader providing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Its intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. This role is for a Machine Learning Engineer to help build cutting edge ML infrastructure for building and serving LLMs at Moveworks. This position is critical in building, optimizing, and scaling end-to-end machine learning systems. The ML infra team covers a variety of responsibilities including distributed training and inference pipelines for large language models (LLM), model evaluation and monitoring frameworks, and LLM latency optimization. These frameworks serve as a strong foundation for hundreds of ML and NLP models in production, serving hundreds of millions of enterprise employees. The role involves solving challenges related to scalability of services and optimization of core algorithms, working closely with machine learning, data infrastructure, and core skill teams. The work will directly impact the way customers experience AI and is critical to the long-term scalability of the core AI product and the company.
Requirements
- 5+ years of industry experience in Machine Learning, Infrastructure or related fields
- Experience with deep learning framework such as Pytorch or Huggingface or LLM serving frameworks such as vLLM or TensorRT-LLM.
- Experience with building and scaling end-to-end machine learning systems
- Experience building scalable micro services and ETL pipelines
- Expertise in Python and experience with performant language such as C++ or GoLang
- Bachelor's in Computer Science, Computer Engineering, Mathematics, or equivalent field.
- A love of research publications in the machine learning and software engineering communities
- Effective communicator with experience collaborating cross-functionally with other teams
Responsibilities
- Design, build and optimize scalable machine learning infrastructure to support training, evaluation, and deployment of large language models.
- Build abstractions to automate various steps in different ML workflows
- Collaborate with cross functional teams of engineers, data analytics, machine learning experts, and product to build new features
- Leverage your experience to drive best practices in ML and data engineering
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
5,001-10,000 employees
