Machine Learning Engineer, ML Exploration

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Machine Learning Engineer, ML Exploration

Stripe

• USD 190K-280K
• Full Time
• Toronto, South San Francisco HQ, or Seattle
• Remote

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. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

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, including but not limited to models that mitigate risks across Stripe’s products and services globally, and models that help our customers to fight fraud by leveraging Stripe’s user facing products like Radar and Identity.

ML is a top priority for Stripe in the coming years. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure.

As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production. You will also have the opportunity to contribute to and influence ML architecture at Stripe as well as be a part of a larger ML community.

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

We are looking for ML Engineers who are passionate about using ML to improve products and delight customers. You have experience developing streaming feature pipelines, building ML models, and deploying them to production, even if it involves making substantial changes to backend code. You are comfortable with ambiguity, love to take initiative, and have a bias towards action.

• 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, Spark

• 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

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. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.

A remote location, in most cases, 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, our expectation is you would regularly work from home rather than a Stripe office. Stripe…