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Machine Learning Engineer, Payment Intelligence

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Stripe

5d ago

  • Job
    Full-time
    Mid & Senior Level
  • Data
    Software Engineering
  • Toronto

AI generated summary

  • You should have 3+ years in ML applications, 2+ years managing ML models, an advanced quantitative degree, and experience in payments or fraud. Proficiency in Python, Java, or Ruby is essential.
  • You will design and deploy fraud detection models, develop features, integrate signals into ML pipelines, collaborate cross-functionally, ensure code quality, and mentor junior engineers.

Requirements

  • Over 3+ years industry experience building machine learning applications in large scale distributed systems.
  • 2+ year of experience working within a team responsible for developing, managing, and optimizing ML models or ML infrastructure
  • Experience designing and training machine learning models to solve critical business problems
  • Experience performing analysis, including querying data, defining metrics, or slicing and dicing data to model performance and business metrics
  • An advanced degree in a quantitative field (e.g. stats, physics, computer science)
  • Proven track record of building and deploying machine learning systems that have effectively solved critical business problems
  • Experience in adversarial domains like Payments, Fraud, Trust, or Safety
  • Experience working in Python, Java and / or Ruby codebases
  • Experience in software engineering in a production environment.

Responsibilities

  • Design and deploy new models using tools (such as Spark, Presto, XGBoost, Tensorflow, PyTorch) and iteratively improve verification and fraud models to protect millions of users from fraud
  • Envision and develop new models for fraud detection i.e work with large payment datasets to find creative new methods of detecting and deterring fraudulent behavior.
  • Propose new feature ideas and design real-time data pipelines to incorporate them into our models.
  • Integrate new signals into ML pipelines, derive new ML features, and build workflows to make this process fast
  • Integrate new models and behaviors into Stripe’s core payment flow
  • Collaborate and execute projects cross-functionally with the data science, product management, infrastructure, and risk teams
  • Ensure engineering outcomes meet or exceed established standards of excellence in code quality, system design, and scalability
  • Mentor engineers earlier in their technical careers to help them grow
  • Propose and implement innovative product ideas to reduce costs and combat fraud at Stripe

FAQs

What is the role of a Machine Learning Engineer in the Payment Intelligence team?

The Machine Learning Engineer in the Payment Intelligence team is responsible for owning the end-to-end lifecycle of applied ML model development and deployment for consumer-facing products like Radar, Adaptive Acceptance, and Identity. They will design, build, and operate Stripe's ML-powered payment decisioning systems.

What tools and technologies will I be expected to use?

You will be expected to use tools such as Spark, Presto, XGBoost, TensorFlow, and PyTorch for designing and deploying machine learning models, as well as for improving verification and fraud models.

What qualifications are required to apply for this position?

The minimum requirements include over 3+ years of industry experience building machine learning applications in large-scale distributed systems, 2+ years of experience in managing ML models, and experience in performing data analysis to model performance and business metrics.

Is an advanced degree necessary for this role?

An advanced degree in a quantitative field is preferred but not required. The focus is on relevant experience and skill set.

How does Stripe balance remote and in-office work?

Stripe offers a hybrid work model where office-assigned employees are expected to spend at least 50% of their time in the local office. Remote employees typically work from home but are encouraged to come to the office for team meetings and events as needed.

What is the salary range for this position?

The annual US base salary range for this role is $211,200 - $316,800, and this may include several career levels at Stripe. The final salary will be determined based on experience, qualifications, and location.

Are benefits included with this position?

Yes, additional benefits may include equity, company bonuses, a 401(k) plan, and medical, dental, and vision benefits, along with wellness stipends.

Will I have opportunities for mentorship in this role?

Yes, you will have the opportunity to mentor engineers who are earlier in their careers, helping them grow technically.

What types of projects will I work on?

You will work on projects related to developing and optimizing machine learning models, improving fraud detection systems, proposing new features, and integrating new signals into ML pipelines.

Stripe

Help increase the GDP of the internet.

Technology
Industry
1001-5000
Employees
2010
Founded Year

Mission & Purpose

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. Headquartered in San Francisco and Dublin, the company aims to increase the GDP of the internet.