Moveworks is looking for a Machine Learning Engineer to help build cutting edge ML infrastructure for building and serving LLM’s. This role will be 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 pipeline for large language models(LLM), model evaluation and monitoring framework, LLM latency optimization, etc. These frameworks serve as a strong foundation for our hundreds of ML and NLP models in production serving hundreds of millions of enterprise employees. We are solving many challenges on scalability of services as well as optimization of core algorithms.
Requirements
- 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
- Experience with ML Inference optimization using TensorRT.
- Experience with distributed training frameworks such as Deepspeed.
- Experience in managing and scaling GPU Inference services via Kubernetes
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
- Leverage your experience to drive best practices in ML and data engineering
- building, optimizing and scaling end-to-end machine learning systems
- distributed training and inference pipeline for large language models(LLM)
- model evaluation and monitoring framework
- LLM latency optimization
Other
- 2+ years of industry experience in Machine Learning, Infrastructure or related fields
- Collaborate with cross functional teams of engineers, data analytics, machine learning experts, and product to build new features
- Effective communicator with experience collaborating cross-functionally with other teams
- A love of research publications in the machine learning and software engineering communities
