Moveworks
Overview
We are looking for a Machine Learning Engineer to help build cutting edge ML infrastructure for building and serving LLMs at Moveworks. This role is critical in building, optimizing and scaling end-to-end machine learning systems. The ML infra team covers distributed training and inference pipelines for large language models (LLMs), model evaluation and monitoring framework, LLM latency optimization, and related tasks. These frameworks serve as a foundation for hundreds of ML and NLP models in production serving hundreds of millions of enterprise employees. We are solving challenges in scalability of services and optimization of core algorithms. In this role you will work closely with our machine learning team, data infrastructure team, and other core teams. Your work will impact the way our customers experience AI and is essential to the long term scalability of our core AI product. 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, we should have a conversation.
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.
What You Bring To The Table (Qualifications)
2+ years of industry experience in Machine Learning, Infrastructure or related fields. Experience with deep learning frameworks such as PyTorch or Hugging Face, or LLM serving frameworks such as vLLM or TensorRT-LLM. Experience with building and scaling end-to-end machine learning systems. Experience building scalable microservices and ETL pipelines. Expertise in Python and experience with performant languages such as C++ or Go. Bachelor's in Computer Science, Computer Engineering, Mathematics, or equivalent field. Interest in research publications in the machine learning and software engineering communities. Effective communicator with experience collaborating cross-functionally with other teams.
Nice To Haves
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.
Base salary compensation range:
$200,000 - $275,000 *Our compensation package includes a market competitive salary, equity for all full time roles, exceptional benefits, and, for applicable roles, commissions or bonus plans. Ultimately, in determining pay, final offers may vary from the amount listed based on geography, the role’s scope and complexity, the candidate’s experience and expertise, and other factors.
Moveworks is an Equal Opportunity Employer. We provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other characteristics protected by law.
Who We Are
Moveworks is an AI Assistant that helps all employees find information, automate tasks, and be more productive. We enable developers to build and deploy AI agents that bring Moveworks capabilities to enterprise processes. It’s powered by a Reasoning Engine paired with an Agentic Automation Engine to handle complex requests by understanding queries and executing intelligent plans — in seconds.
Founded in 2016, Moveworks has raised $315M in funding and achieved significant milestone in ARR in 2024. We’ve been recognized in various industry lists and awards, reflecting our growth and impact. Today, Moveworks has over 500 employees in six offices globally and is backed by leading investors. Come join one of the most innovative teams on the planet!
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We are looking for a Machine Learning Engineer to help build cutting edge ML infrastructure for building and serving LLMs at Moveworks. This role is critical in building, optimizing and scaling end-to-end machine learning systems. The ML infra team covers distributed training and inference pipelines for large language models (LLMs), model evaluation and monitoring framework, LLM latency optimization, and related tasks. These frameworks serve as a foundation for hundreds of ML and NLP models in production serving hundreds of millions of enterprise employees. We are solving challenges in scalability of services and optimization of core algorithms. In this role you will work closely with our machine learning team, data infrastructure team, and other core teams. Your work will impact the way our customers experience AI and is essential to the long term scalability of our core AI product. 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, we should have a conversation.
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.
What You Bring To The Table (Qualifications)
2+ years of industry experience in Machine Learning, Infrastructure or related fields. Experience with deep learning frameworks such as PyTorch or Hugging Face, or LLM serving frameworks such as vLLM or TensorRT-LLM. Experience with building and scaling end-to-end machine learning systems. Experience building scalable microservices and ETL pipelines. Expertise in Python and experience with performant languages such as C++ or Go. Bachelor's in Computer Science, Computer Engineering, Mathematics, or equivalent field. Interest in research publications in the machine learning and software engineering communities. Effective communicator with experience collaborating cross-functionally with other teams.
Nice To Haves
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.
Base salary compensation range:
$200,000 - $275,000 *Our compensation package includes a market competitive salary, equity for all full time roles, exceptional benefits, and, for applicable roles, commissions or bonus plans. Ultimately, in determining pay, final offers may vary from the amount listed based on geography, the role’s scope and complexity, the candidate’s experience and expertise, and other factors.
Moveworks is an Equal Opportunity Employer. We provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other characteristics protected by law.
Who We Are
Moveworks is an AI Assistant that helps all employees find information, automate tasks, and be more productive. We enable developers to build and deploy AI agents that bring Moveworks capabilities to enterprise processes. It’s powered by a Reasoning Engine paired with an Agentic Automation Engine to handle complex requests by understanding queries and executing intelligent plans — in seconds.
Founded in 2016, Moveworks has raised $315M in funding and achieved significant milestone in ARR in 2024. We’ve been recognized in various industry lists and awards, reflecting our growth and impact. Today, Moveworks has over 500 employees in six offices globally and is backed by leading investors. Come join one of the most innovative teams on the planet!
#J-18808-Ljbffr