Senior Software Engineer, ML Platform Engineer

Summary

Join Xometry's core machine learning platform engineering team as a Senior Backend Software Engineer! This 1-year contract position involves designing, developing, and deploying AI/ML infrastructure. You will collaborate with data scientists and machine learning engineers, ensuring the scalability and security of our platform. Responsibilities include code review, documentation, and participation in an on-call rotation. The ideal candidate possesses extensive experience in software engineering, Python, Terraform, and AWS, along with a strong understanding of software engineering fundamentals. This is a remote position.

Requirements

• 5+ years of experience in a fast-paced technical, problem-solving environment as a software or machine learning engineer
• Attention to detail, good work ethic, ability to work on multiple projects simultaneously, and strong communication skills
• Demonstrable understanding of software engineering fundamentals related to security, scalability, asynchronous programming and transactions
• Knowledge and demonstrated experience developing in Python and Terraform for AWS
• Knowledge and demonstrated experience deploying infrastructure as code (IaC)
• Experience with software engineering principles

Responsibilities

• Design, develop, test, and release software and infrastructure supporting AI/ML and experimentation workflows
• Grow our knowledgebase by participating in code reviews, writing, and reviewing documentation
• Work closely with other engineers and product managers to become a valued member of an autonomous, cross-functional team
• Be responsible for the services that are owned by our team, including deploying services into AWS and Kubernetes environments and taking part in an on-call rotation
• Stay up-to-date on the latest technologies and pro-actively identify opportunities for growth

Preferred Qualifications

• Experience with build and testing ci/cd pipelines using Github Actions
• Knowledge of the machine learning lifecycle, including best practices in MLOps
• Experience deploying data science or machine learning solutions
• Demonstrated knowledge of principles of service-oriented architectures and ability to lead efforts in defining and implementing a service strategy
• Experience with relational and/or NoSQL databases with understanding of Normalization/Denormalization, Constraints, Transactions, Replication, and Sharding
• Experience communicating technical concepts to non-technical stakeholders

Benefits

#LI-Remote