Machine Learning Engineer, Capital Underwriting

About the role

Stripe Capital provides access to fast, flexible financing to small-and-medium businesses on Stripe to accelerate their growth. As a machine learning engineer for Stripe Capital, you'll design, build, train, evaluate, deploy, and own ML models in production to provide financing opportunities to as many users as possible while satisfying financial performance goals. You'll work closely with software engineers, data scientists, product managers, and risk managers to operate Stripe's ML-powered systems, features, and products.

Responsibilities

• Design state-of-the-art ML models and large scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints
• Design systems to speed up the time from idea to deployment of new models
• Experiment and iterate on ML models (using tools such as PyTorch and TensorFlow) to achieve key business goals and drive efficiency
• Develop pipelines and automated processes to train and evaluate models in offline and online environments
• Integrate ML models into production systems and ensure their scalability and reliability
• Collaborate with product and strategy partners to propose, prioritize, and implement new product features
• Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions

Requirements

• 5+ years of industry experience building and shipping ML systems in production
• Proficient with ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark
• Hands-on experience in designing, training, and evaluating machine learning models
• Hands-on experience in productionizing and deploying models at scale
• Hands-on experience in orchestrating complicated data pipelines and efficiently leveraging large-scale datasets

Qualifications

• MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics)
• Proven track record of building and deploying ML systems that have effectively solved ambiguous business problems
• Experience in adversarial domains such as Lending, Trading, Fraud
• Experience with Deep Learning including the latest architectures such as transformers, test-time compute, reinforcement learning

Skills

• Strong understanding of machine learning algorithms and techniques
• Experience with large-scale data processing and analysis
• Ability to work in a fast-paced, dynamic environment
• Excellent communication and collaboration skills

Benefits

• Annual US base salary range: $180,000 - $270,000
• Equity, company bonus or sales commissions/bonuses
• 401(k) plan
• Medical, dental, and vision benefits
• Wellness stipends

Pay

The annual US base salary range for this role is $180,000 - $270,000. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location.

Schedule

Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India, and Dublin, Ireland work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible.