Senior Software Engineer, ML Platform Engineer
Xometry
πRemote - Argentina
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Job highlights
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 state-of-the-art solutions. Responsibilities include software development, code review, and collaboration within a cross-functional team. You will own services deployed in AWS and Kubernetes environments and participate in on-call rotations. Continuous professional development is encouraged. 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
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