Principal ML Platform Engineer - Remote

Upstart; United States; Remote; USD 220,700 - 300,000; Full time

Benefits offered by this job

Health coverage

401(k)

Employee Stock Purchase Plan (ESPP)

Paid time off

Wellness resources

Wellness allowance

In‑person onboarding/offices access

Job summary

Upstart seeks a Principal Machine Learning Engineer to shape and scale ML platforms across the company. You will collaborate with researchers, data scientists, and ML platform engineers to build scalable tools and systems that accelerate model development and improve predictive accuracy across fintech products.

You will lead end‑to‑end ML lifecycle initiatives, from data prep to deployment, while driving architectural decisions and platform improvements that enable fast, reliable experimentation

Qualifications

• Strong theoretical and practical foundation in machine learning and statistics.
• Ability to reason from first principles about model assumptions, bias, uncertainty, and evaluation.
• Deep understanding of production ML beyond frameworks and ability to apply this knowledge to production solutions.
• 5–7+ years of hands‑on experience in applied machine learning and production‑scale modeling.
• Experience in fintech, pricing, or risk modeling in ML‑driven products.
• Proficiency in Python and core ML frameworks (PyTorch, TensorFlow, Scikit‑learn, XGBoost).
• Ability to lead technical direction in ambiguous, high‑impact domains.
• Experience collaborating with cross‑functional teams including ML scientists, engineers, and product partners.
• Master’s or PhD in a quantitative field, or equivalent experience.
• End‑to‑end model development: data prep, feature engineering, training, evaluation, deployment.

Responsibilities

• Develop and scale ML infrastructure, embeddings platform, and tooling for model training and serving.
• Lead feature engineering pipelines to accelerate signal development and reduce manual steps.
• Build automated continuous‑learning systems with data refresh, retraining, and drift monitoring.
• Scale training pipelines for larger datasets and faster experimentation.
• Collaborate with Data Engineering, ML Platform, Pricing and other teams for end‑to‑end ML systems.
• Guide engineering initiatives turning modeling needs into scalable infrastructure.
• Improve accuracy and reliability of ML outcomes across Upstart's platform.

Skills

Machine learning

Statistics

Python

Production-scale ML

Cross-functional collaboration

Communication

CUDA/GPU acceleration

Education

Master's or PhD in a quantitative discipline

Tools

PyTorch

TensorFlow

Scikit-learn

XGBoost

CUDA

Job description

Upstart seeks a Principal Machine Learning Engineer to shape and scale ML platforms across the company. You will collaborate with researchers, data scientists, and ML platform engineers to build scalable tools and systems that accelerate model development and improve predictive accuracy across fintech products.

You will lead end‑to‑end ML lifecycle initiatives, from data prep to deployment, while driving architectural decisions and platform improvements that enable fast, reliable experimentation