Machine Learning Engineer, ML Exploration

SuprAIJobs; Toronto (SD); Hybrid; USD 192,000 - 288,000; Full time

Benefits offered by this job

Equity

401(k)

Medical, dental & vision

Wellness stipends

Job summary

Stripe is seeking a Machine Learning Engineer to join the ML Infrastructure team in building and operating AI models that support Stripe's products globally. You will analyze opportunities, train models, run experiments, and deploy pipelines to production while influencing ML architecture across the company.

You will design feature pipelines, improve evaluation and monitoring, and collaborate with stakeholders to deliver end-to-end projects using XGBoost, TensorFlow and PyTorch in a

Qualifications

• 5+ years of industry experience in end-to-end ML development and production deployment.
• Advanced degree in a quantitative field (e.g. CS, statistics, physics).
• Proficient in Python, Scala, Spark.

Responsibilities

• Design, train, and deploy ML models using modern frameworks.
• Iterate on feature pipelines and data processing to improve model performance.
• Collaborate with teams to drive end-to-end ML projects from idea to production.
• Build and monitor ML systems to ensure reliability and scalability.
• Contribute to ML architecture decisions and best practices at Stripe.

Skills

Python

Scala

Spark

Education

Advanced degree in a quantitative field

Tools

XGBoost

TensorFlow

PyTorch

Job description

Back

Machine Learning Engineer, ML Exploration

Stripe

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

Job Description

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - 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.

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, 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.

What You'll Do

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.

Responsibilities

• 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.

Who You Are

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.

Minimum 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, 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.

Hybrid work at Stripe

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 does not cover the cost of relocating to a remote location. We encourage you to apply for roles that match the location where you currently or plan to live.

Pay And Benefits

The annual US base salary range for this role is $192,000 - $288,000. 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. 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.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.