Senior Machine Learning Engineer, Agentic Systems - Moveworks

ServiceNow•Mountain View, CA

2h•$161,300 - $274,200•Onsite

About The Position

Moveworks is seeking a Senior Machine Learning Engineer to join their Agentic Systems team. This role is crucial for building and scaling cutting-edge ML infrastructure, particularly for training, serving, and optimizing Large Language Models (LLMs). The ML infra team is responsible for distributed training and inference pipelines, model evaluation and monitoring frameworks, and LLM latency optimization. These systems form the foundation for hundreds of ML and NLP models in production, serving millions of enterprise employees. The role involves solving challenges related to service scalability and core algorithm optimization. The engineer will collaborate with machine learning, data infrastructure, and other core teams, with their work directly impacting customer experience with AI and the long-term scalability of the core AI product. This is a high-impact, fast-moving role focused on building and productionizing state-of-the-art ML infrastructure.

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