Senior Machine Learning Engineer, Moveworks

• 2+ 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

Desirable

• We are looking for a Machine Learning Engineer to help build cutting edge ML infrastructure for building and serving LLM’s at Moveworks
• 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
• In this role you will work closely with our machine learning team, data infrastructure team and every core skill
• Above all, your work will impact the way our customers experience AI
• Put another way, this role is absolutely critical to the long term scalability of our core AI product and ultimately the company
• You will be responsible for building and productionizing ML infrastructure that runs state of the art models
• If you are looking for a high-impact, fast-moving role to take your work to the next level, we should have a conversation
• 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