Principal Machine Learning Engineer

Upstart

5d•Remote

About The Position

At Upstart, we’re united by a mission that matters: to radically reduce the cost and complexity of borrowing for all Americans. Every day, we bring creativity, experimentation, and advanced AI to reshape access to credit, helping millions move forward financially with clarity and confidence. As the leading AI lending marketplace, we partner with banks and credit unions to expand access to affordable credit through technology that’s both radically intelligent and deeply human. Our platform runs over one million predictions per borrower using more than 1,800 signals, powering smarter, fairer decisions for millions of customers. But the numbers only hint at the impact. Every idea, every voice, and every contribution moves us closer to a world where credit never stands between people and their financial progress. We’re proudly digital-first, giving most Upstarters the flexibility to do their best work from wherever they thrive, alongside teammates across 80+ cities in the US and Canada. Digital-first doesn’t mean distant. We’re intentional about in-person connection through team onsites, planning sessions, and moments that spark creativity and trust. And whether you choose to work primarily from home or collaborate in-person from one of our offices in Columbus, Austin, the Bay Area, or New York City (opening Summer 2026), you’ll have the support to work in the way that works best for you. If you’re energized by tackling meaningful problems, excited to innovate with purpose, and motivated by work that truly matters, we’d love to hear from you. The Team The Machine Learning Platform team builds the foundational technology that scales machine learning innovation across Upstart. As a Principal Machine Learning Engineer, you will work at the intersection of applied ML and platform engineering—collaborating closely with Research Scientists, Data Scientists, and ML Platform Engineers to design tools and systems that accelerate model development to ultimately improve predictive accuracy. Success in this role requires deep knowledge of ML throughout the entire modeling lifecycle - from data preparation to training and deployment to production. In this role, you will lead engineering initiatives that turn high-impact modeling needs into scalable, reusable infrastructure. This includes building a unified embeddings platform for training, serving, and managing representations at scale; streamlining feature engineering pipelines to reduce manual steps and deliver new signals quickly; developing automated continuous-learning systems that handle data refresh, retraining, evaluation, and drift monitoring with minimal manual effort; and scaling our training pipelines to support larger datasets, more complex architectures, and faster experimentation. Across all of these efforts, you will work backward from applied ML projects that meaningfully improve accuracy—using those real-world scenarios to harden the platform capabilities that enable ML teams across Upstart to innovate with greater speed, reliability, and impact. This is a high influence role suited for those who enjoy combining science innovation, with cross functional collaboration and advisory.

Requirements

7+ years of hands-on experience in applied machine learning, with strong exposure to production-scale modeling efforts.
Demonstrated expertise in end-to-end model development: data prep, 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 (e.g., PyTorch, TensorFlow, Scikit-learn, 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.
Numerically-savvy and smart with ability to operate at a fast pace
Master’s degree or PhD in a quantitative discipline, or equivalent additional professional experience.

Nice To Haves

Practical experience optimizing ML workflows using CUDA/GPU acceleration.
Background in feature store design, embedding architecture, or synthetic data generation for model training.
Proven track record of improving model accuracy in production environments with measurable business outcomes.
Familiarity with modern experimentation frameworks, hyperparameter tuning tools, and automated model selection techniques.

Responsibilities

Scale ML innovation by building tools, infrastructure, and workflows that dramatically improve the speed and reliability of model development.
Work backward from modeling needs to design systems that directly unlock gains in accuracy, efficiency, and scientific productivity.
Explore new algorithms and methodologies for our machine learning models and develop tooling to support them
Improve the entire ML lifecycle—from data readiness and feature development through training, evaluation, serving, and monitoring.
Automate and standardize operational workflows, enabling scientists to focus on high-leverage modeling and analysis rather than manual pipelines.
Define the roadmap for our next generation ML Platform, balancing near-term impact with long-term architectural scalability.
Collaborate cross-functionally with Data Engineering, ML Platform, Pricing, and other teams to build reliable, end-to-end ML systems.
Your work will multiply the effectiveness of every ML team at Upstart—accelerating innovation and advancing our mission to make credit more accurate, accessible, and fair.
This is a high influence role suited for those who enjoy combining science innovation, with cross functional collaboration and advisory.

Benefits

Competitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly
Generous 401(k) plan with Upstart matching $2 for every $1 contributed, up to $15,000 per year
Employee Stock Purchase Plan (ESPP) with discounted stock purchase options for eligible employees
Affordable medical, dental, and vision coverage, with multiple plan options - Upstart covers 90% to 100% of the cost depending on the plans you choose
Health Savings Account contributions from Upstart for eligible plans
Income protection benefits, including company-paid Basic Life, AD&D, and Short- and Long-Term Disability coverage, with options to purchase supplemental coverage
Paid time off, sick and safe time, and company holidays
Paid family and parental leave to support caregiving and major life moments
Family-centered benefits through Carrot and Cleo, supporting fertility, parenthood, and caregiving
Employee Assistance Program (EAP) offering mental health support and life-centered resources
Financial wellness resources, including access to financial planning tools and a financial concierge service
Annual wellness allowance to support your physical and emotional well-being and personal development, based on what matters most to you
Annual productivity allowance to invest in relevant tools and resources you need to do your best work, no matter where you work from
Connection and community through team events and onsites, all-company updates, and employee resource groups (ERGs)
Onsite perks, including catered lunches and fully stocked micro-kitchens when working from one of our four offices, located in the Bay Area, Austin, Columbus, and New York City (opening Summer 2026!).