Senior ML Platform Engineer (Remote)

United States Digital Space LLC; United States; Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Remote work-friendly policy

Opportunities for in-person on-sites

Job summary

United States Digital Space LLC is seeking a Principal Machine Learning Engineer to advance production ML platforms across data science, engineering, and product teams.

You will design scalable embeddings, automate data refresh and monitoring, and guide the ML lifecycle from data prep to deployment, enabling faster iteration and higher model quality. Remote-US role with regular on-sites optional.

Qualifications

• Strong theoretical and practical foundation in machine learning and statistics.
• Ability to reason from first principles about model assumptions, bias, uncertainty, tradeoffs, evaluation, and failure modes.
• A deep understanding of model behavior beyond tool abstractions and how to apply it to production solutions.
• 5-7+ years of hands‑on experience in applied machine learning, with production-scale modeling.
• Experience in fintech, pricing, or risk modeling is a plus.
• Proficiency in Python and core ML frameworks (PyTorch, TensorFlow, Scikit‑learn, XGBoost).
• Ability to lead direction in ambiguous, high-impact domains.

Responsibilities

• Scale ML platform tooling and infrastructure to accelerate model development.
• Design systems that improve accuracy, efficiency, and scientific productivity.
• Explore algorithms and tooling to support experimental ML work.
• Oversee end‑to‑end ML lifecycle from data prep to deployment and monitoring.
• Collaborate with data engineers, ML platform, pricing, and product teams.

Skills

Machine learning fundamentals

Statistics

Production ML systems

Python programming

Cross-functional collaboration

Leadership

Model evaluation & monitoring

Education

Master's degree or PhD in a quantitative discipline

Tools

Python

PyTorch

TensorFlow

Scikit-learn

XGBoost

Job description

United States Digital Space LLC is seeking a Principal Machine Learning Engineer to advance production ML platforms across data science, engineering, and product teams.

You will design scalable embeddings, automate data refresh and monitoring, and guide the ML lifecycle from data prep to deployment, enabling faster iteration and higher model quality. Remote-US role with regular on-sites optional.