Machine Learning Engineer, ML Exploration

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead.

About the team

The Machine Learning Infrastructure group at Stripe aims to provide state-of-the-art infrastructure and support for building and operationalizing AI/ML models for all business verticals within the company. This includes models that mitigate risks across Stripe’s products and services globally, and models that help customers fight fraud by leveraging Stripe’s user-facing products like Radar and Identity. ML is a top priority for Stripe, and we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure.

Responsibilities

• Designing, training, improving, and launching machine learning models using tools such as XGBoost, TensorFlow, and PyTorch.
• Proposing and implementing ideas that directly impact Stripe’s top-line metrics.
• Proposing new feature ideas and designing data pipelines to incorporate them into our models.
• Improving the way we evaluate and monitor our model and system performance.
• Collaborating with stakeholders and driving end-to-end projects involving a variety of technologies and systems to successful completion.

Requirements

• At least 5 years of industry experience doing end-to-end ML development on a machine learning team and bringing ML models to production.
• Advanced degree in a quantitative field (e.g., computer science, statistics, physics).
• Proficient in Python, Scala, and Spark.

Preferred Qualifications

• 5+ years of experience in full-time software development roles.
• Hands-on applied ML (model training, deployment to production, etc.) experience.
• You keep up-to-date on the latest in AI engineering practices and research.
• Knowledge about driving a hypothesis from data.
• Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis.
• Experience evaluating niche and upcoming ML solutions.

Schedule

This role is available either in an office or a remote location (typically, 35+ miles or 56+ km from a Stripe office). Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. A remote location is defined as being 35 miles (56 kilometers) or more from one of our offices. While you would be welcome to come into the office for team/business meetings, on-sites, meet-ups, and events, the expectation is you would regularly work from home rather than a Stripe office. Stripe does not cover the cost of relocating to a remote location.

Pay

The annual US base salary range for this role is $192,000 - $288,000. This range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.

Benefits

• Equity
• Company bonus or sales commissions/bonuses
• 401(k) plan
• Medical, dental, and vision benefits
• Wellness stipends