Software Engineer - Machine Learning Infrastructure

Software Engineer - Machine Learning Infrastructure
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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.
Your role & responsibilities:
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.
Your skills & qualifications:
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.