Senior Machine Learning Engineer, Agentic Systems - Moveworks

ServiceNow•Mountain View, CA

1d•Hybrid

About The Position

Moveworks is seeking a Machine Learning Engineer to join their Agentic AI Assistant platform team. This role is crucial for building, optimizing, and scaling end-to-end machine learning systems, specifically focusing on distributed training and inference pipelines for large language models (LLMs), model evaluation and monitoring frameworks, and LLM latency optimization. The work will support hundreds of ML and NLP models in production, serving millions of enterprise employees and addressing challenges in service scalability and core algorithm optimization. The position is critical to the long-term scalability of the core AI product and the company's success. The engineer will work closely with machine learning, data infrastructure, and other core teams, with their work directly impacting customer experience with AI.

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.