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Principal Machine Learning Engineer

1 day, 17 hours ago
United States
Full-time
Lead
Machine Learning Engineer
Software Development
Feature Engineering Machine Learning Python PyTorch Scikit-learn TensorFlow XGBoost
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Upstart

Upstart

Upstart Powered Loans: Personal, Car Refinance & Consolidation Through Upstart, apply online for a fast personal loan, auto refinancing, or debt consolidation. Try our quick rate check today with no impact to your credit! Founded by ex Googlers, Upstar...

Banks
1K-5K
Founded 2012
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Description

  • Lead engineering initiatives that translate applied machine learning needs into scalable, reusable platform infrastructure.
  • Design and build a unified embeddings platform for training, serving, and managing representations at scale.
  • Streamline feature engineering pipelines to reduce manual work and accelerate delivery of new signals.
  • Develop automated continuous-learning systems for data refresh, retraining, evaluation, and drift monitoring.
  • Scale training pipelines to support larger datasets, more complex models, and faster experimentation.
  • Improve the machine learning lifecycle across data readiness, feature development, training, evaluation, serving, and monitoring.
  • Explore new algorithms and methodologies for machine learning models and develop supporting tooling.
  • Define the roadmap for the next generation ML Platform with both near-term impact and long-term scalability in mind.
  • Collaborate cross-functionally with Data Engineering, ML Platform, Pricing, Research Scientists, Data Scientists, and product partners.
  • Automate and standardize operational workflows so scientists can focus on higher-leverage modeling and analysis.

Requirements

  • 7+ years of hands-on experience in applied machine learning with exposure to production-scale modeling efforts.
  • Demonstrated experience across the full model development lifecycle, including data preparation, feature engineering, training, evaluation, and deployment.
  • Experience working in high-scale, ML-driven product environments, especially in fintech, pricing, or risk modeling.
  • Proficiency in Python and core ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or XGBoost.
  • Ability to work autonomously and lead technical direction in ambiguous, high-impact domains.
  • Experience collaborating with cross-functional teams including ML scientists, engineers, and product partners.
  • Ability to bridge engineering and science teams and influence technical strategy across disciplines.
  • Strong numerical aptitude and the ability to operate effectively at a fast pace.
  • Master’s degree or PhD in a quantitative discipline, or equivalent additional professional experience.
  • Preferred: practical experience optimizing ML workflows using CUDA/GPU acceleration.
  • Preferred: background in feature store design, embedding architecture, or synthetic data generation for model training.
  • Preferred: track record of improving model accuracy in production environments with measurable business outcomes.
  • Preferred: familiarity with experimentation frameworks, hyperparameter tuning tools, and automated model selection techniques.

Benefits

  • Anticipated base salary range of $220,700 to $300,000 USD for U.S. remote candidates.
  • Target bonuses and annual equity grants that vest quarterly.
  • Generous 401(k) with company match of $2 for every $1 contributed, up to $15,000 per year.
  • Employee Stock Purchase Plan with discounted stock purchase options for eligible employees.
  • Affordable medical, dental, and vision coverage, with Upstart covering 90% to 100% of plan costs depending on the option selected.
  • Health Savings Account contributions for eligible plans.
  • Company-paid life, AD&D, and short- and long-term disability coverage, with options for supplemental coverage.
  • Paid time off, sick and safe time, and company holidays.
  • Paid family and parental leave.
  • Employee Assistance Program with mental health support and life-centered resources.
  • Annual wellness allowance and annual productivity allowance.
  • Financial wellness resources, including financial planning tools and a financial concierge service.
  • Hybrid digital-first flexibility with the option to work from home or from offices in the Bay Area, Austin, Columbus, or New York City.
  • Onsite perks such as catered lunches and stocked micro-kitchens when working from an office.

Interested in this position?

Apply directly on the company website

Apply Now

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