Machine Learning Engineer, Supportability
Who we are About Stripe 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.
What this role actually needs.
Who we are About Stripe 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. Responsibilities: - Design state-of-the-art AI/ML models and large scale systems for detection and decisioning for Stripe products based onAI/ML principles, domain knowledge, and engineering constraints - Drive the expansion of Stripe's largest LLM-based system, scaling its usage and integrating new capabilities through agentic approaches or supervised learning. - Rapidly prototype new AI/ML-based approaches to achieve key business goals. - Develop processes to train and evaluate models in offline and online environments - Integrate models into production systems and ensure their scalability and reliability - Collaborate with product and strategy partners to propose, prioritize, and implement new product features Requirements: - 2+ years of industry experience building and shipping AI/ML systems in production - Proficient with AI/ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark - Knowledge of various AI/ML algorithms and model architectures - Hands-on experience in designing, training, and evaluating machine learning models - Hands-on experience in productionizing and deploying models at scale - Experience rigorously evaluating model performance, including cleaning data, and working with data-generating processes to improve signal and reduce noise in high-noise datasets. Company context: Stripe builds financial infrastructure for internet businesses, with strong hiring across platform, product, data, and AI-adjacent teams.
Day-to-day expectations
Stripe lists these responsibilities for the Machine Learning Engineer, Supportability role.
- Design state-of-the-art AI/ML models and large scale systems for detection and decisioning for Stripe products based onAI/ML principles, domain knowledge, and engineering constraints
- Drive the expansion of Stripe's largest LLM-based system, scaling its usage and integrating new capabilities through agentic approaches or supervised learning.
- Rapidly prototype new AI/ML-based approaches to achieve key business goals.
- Develop processes to train and evaluate models in offline and online environments
- Integrate models into production systems and ensure their scalability and reliability
- Collaborate with product and strategy partners to propose, prioritize, and implement new product features
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 2+ years of industry experience building and shipping AI/ML systems in production
- Proficient with AI/ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark
- Knowledge of various AI/ML algorithms and model architectures
- Hands-on experience in designing, training, and evaluating machine learning models
- Hands-on experience in productionizing and deploying models at scale
- Experience rigorously evaluating model performance, including cleaning data, and working with data-generating processes to improve signal and reduce noise in high-noise datasets.
Why this listing is more than a copied job post.
Machine Learning Engineer, Supportability is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
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Apply through the employer source
Open the source listing from stripe.com, confirm the role is still active, then apply on the employer or ATS page.
Source: stripe.com · Source ID: 7384709 · Confidence: 94/100 · Last checked: May 7, 2026
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