New Grad ML Platform Engineer (Remote)

United States Digital Space LLC; United States; Remote; USD 98,000 - 139,000; Full time

Benefits offered by this job

Medical/dental/vision coverage

Equity refreshers

Remote work reimbursement

Paid time off

Employee assistance programs

Job summary

United States Digital Space LLC is seeking a Software Engineer (New Grad) for its ML team. This remote-first role can be performed from anywhere in the United States or Canada.

You will join a team building and maintaining a large-scale ML platform, enabling production-grade ML models and efficient deployment across a distributed stack. You will work at the intersection of ML, distributed systems, and GPU serving performance, shipping to production in early weeks with mentorship and strong

Qualifications

• 2025 or 2026 graduate with or pursuing a BS, MS, or PhD in Computer Science, Engineering, or a related technical field.
• Interest in large-scale distributed systems, infrastructure, and ML.

Responsibilities

• Help build and maintain the core infrastructure powering the ML platform for high availability, scalability, and performance.
• Develop distributed systems that serve ML models in production, from LRMs to LLMs.
• Work on GPU model serving, optimizing latency, throughput, and cost for larger models.
• Contribute to PyTorch-first standardization and ML ecosystem modernization.
• Improve ML developer velocity by building tooling for easier development, testing, and deployment of models.
• Modernize the feature store to accelerate feature delivery to production.
• Participate in on-call rotation to resolve production issues.

Skills

Python

Go

C++

Distributed systems

Machine learning

Education

Bachelor's/Master's/PhD in CS/Engineering

Tools

Kubernetes

Docker

AWS

Job description

United States Digital Space LLC is seeking a Software Engineer (New Grad) for its ML team. This remote-first role can be performed from anywhere in the United States or Canada.

You will join a team building and maintaining a large-scale ML platform, enabling production-grade ML models and efficient deployment across a distributed stack. You will work at the intersection of ML, distributed systems, and GPU serving performance, shipping to production in early weeks with mentorship and strong