or apply directly on Stripe's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 23 days Stripe's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- No 3% of Stripe's roles list one
- Ghost-job risk at Stripe
- low 0 stale, 52 reposted of 633 open
- Hiring momentum
- 892 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from Stripe's own greenhouse board since 2026-08-03. Full hiring picture for Stripe.
About this role
As a Staff Machine Learning Engineer in the Financial Connections team at Stripe, you will design, train, and deploy machine learning models to enhance the quality and accuracy of financial data. Your role will involve building large-scale ML systems, experimenting with various ML tools, and collaborating with cross-functional teams to identify opportunities for improvement. Additionally, you will mentor other engineers and contribute to the team's ML engineering culture.
- benefits
- 1/5
- freshness
- 4/5
- career value
- 5/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Stripe as an employer.
What you need
- 10+ years of industry experience building and shipping ML systems in production
- Proficient with ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark
- Hands-on experience in designing, training, and evaluating machine learning models
- Hands-on experience in productionizing and deploying models at scale
- Hands-on experience in orchestrating data pipelines and efficiently leveraging large-scale datasets
- Strong collaboration skills and the ability to work across teams and contribute to peers' success
Nice to have
- MS or PhD degree in ML/AI or a related field (e.g., math, physics, statistics, computer science)
- Experience in fintech, open banking, or financial data domains
- Experience with NLP, LLMs, or text classification at scale
- Experience in adversarial or noisy-data domains such as fraud detection, risk modeling, or data quality
- Proven track record of building and deploying ML systems that have effectively solved ambiguous business problems
Worth weighing
- No salary listed
- Role requires significant experience (10+ years) which may limit opportunities for less experienced candidates
- Focus on fintech and financial data may not appeal to all ML engineers
Summarised from Stripe's posting. Read the full original.
Listed by Stripe on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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