← Back to Latest Jobs
Stripe

Machine Learning Engineer

Stripe is looking for a skilled Machine Learning Engineer to join our growing team in South San Francisco. This role centers on utilizing advanced statistical modeling and deep learning techniques to solve some of the industry's most challenging problems in finance and payments. You will be responsible for designing, training, validating, and deploying robust models that enhance fraud detection, optimize payment routing, and improve user experience globally. Key responsibilities include managing large-scale datasets, iterating on model architectures, and establishing best practices within the MLOps lifecycle. Proficiency with modern frameworks (like PyTorch or TensorFlow) and the ability to translate complex business requirements into mathematical models are paramount. Join us to make a tangible impact on global commerce infrastructure.

Stripe South San Francisco, CA, United States

(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)

Preparing

2500

Question set

175

Duration

Permanent

Focus areas

Deep LearningTime Series AnalysisPyTorchData Modeling

People Also Ask (FAQs)

What is the last date to apply for Machine Learning Engineer?

The closing date is listed in the official advertisement — apply as early as possible.

How do I apply for Machine Learning Engineer?

Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.

Is there negative marking in the Stripe test?

The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.

What is the passing marks for this test?

The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.

How can I prepare for the Machine Learning Engineer test?

Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: Deep Learning, Time Series Analysis, PyTorch, Data Modeling.

Quick start

Review the job summary, then jump into prep with the same flow used for exam starts.

Prepare for this test

We use cookies

We use essential cookies to keep the platform running and analytics cookies to understand usage. You can accept or reject analytics and advertising cookies.