Python proficiency with pytorch tensorflow scikit-learn
The role focuses on building a unified embeddings platform and streamlining feature engineering pipelines to reduce manual steps and deliver new signals quickly
Job Summary
The role focuses on building a unified embeddings platform and streamlining feature engineering pipelines to reduce manual steps and deliver new signals quickly.
Candidates will lead initiatives to automate continuous-learning systems that handle data refresh, retraining, evaluation, and drift monitoring with minimal effort.
Upstart offers competitive compensation including base pay, bonus opportunities, annual equity grants, and comprehensive health benefits with a generous 401(k) match.
Matching Summary
The role focuses on building a unified embeddings platform and streamlining feature engineering pipelines to reduce manual steps and deliver new signals quickly.
Salary
Base: $220,700 - $300,000 USD; Bonus/Equity: Target bonuses and annual equity grants vesting quarterly; Benefits: Medical, dental, vision, 401(k) match up to $15,000, ESPP, paid time off
Skills & Requirements
Must-have
7+ years applied machine learning experience
End-to-end model development lifecycle expertise
Python proficiency with PyTorch TensorFlow Scikit-learn
Production-scale modeling in fintech or risk domains
Cross-functional collaboration with data scientists
Nice-to-have
CUDA GPU acceleration optimization experience
Feature store design and embedding architecture background
Proven track record of improving production model accuracy
Experience with automated model selection techniques
Key Requirements
Master's degree or PhD in quantitative discipline
7+ years hands-on experience in applied ML
Demonstrated expertise in end-to-end model deployment