Software Engineer - Machine Learning Infrastructure

Plume’s Data Services team is looking for bright and ambitious ML Infrastructure Engineers to continue delivering industry-leading innovation at a rapid pace. Due to the massive scale requirements of our platform, you will be solving challenging problems on a daily basis using cutting edge technologies and advanced architectural patterns involving distributed systems and stateful services. This is a high impact role with immense growth opportunities and will truly put your software and machine learning engineering skills to the test.

• Create a vision and construct a roadmap to build the fundamental machine learning infrastructure for the Data Science team.
• Develop and deploy scalable tools and services to handle machine learning training and inference.
• Design data pipelines and engineering infrastructure to support our Plume’s machine learning systems at scale.
• Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
• Empower team members to follow the machine learning and software engineering best practices.
• Identify and evaluate new technologies to improve performance, maintainability, and reliability.
• Support model development, with an emphasis on auditability, versioning, and data security.

• Education Requirements: BS/MS/PhD in Computer Science, Electrical Engineering or related technical field.
• 2+ years of industry experience in developing ML systems, with emphasis on MLOps.
• High proficiency in writing idiomatic code in Python and/or Scala.
• Exposure to machine learning and software engineering methodologies and best practices.
• Experience working with cloud computing and database systems, and machine learning technologies, such as AWS RDS, Sagemaker, Lambda, Spark (Databricks), MLFlow, Airflow.
• Experience and demonstrated capability to handle challenges with vague or abstract problem definition.
• Can work asynchronously with teams from different time zones.