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. 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 teamOur Applied ML team aims to reform how our users interact with Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include helping our users resolve issues with Stripe faster or making it easier for our users to sign up and navigate Stripe. We are using the latest LLMs as well as fine-tuning our own models. We're an end-to-end team going from ideas to models to shipping in production. You can learn more about our team’s work from this recent talk.
What you’ll doAs 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.
ResponsibilitiesOur team operates fluidly and here are some problems you may tackle:
- How do we evaluate a system offline & online?
- How do we improve performance to match (and beat) humans?
- How do we ensure model quality doesn’t degrade online?
- Does fine-tuning an LLM give us better performance?
- What are the right OSS and in-house platforms we should invest in?
And in the process you will:
- Develop pipelines and automated processes to train and evaluate models in offline and online environments
- Integrate ML models into production systems and ensure their scalability and reliability
- Collaborate with product and strategy partners to propose, prioritize, and implement new product features
- Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions
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- Have at least 3 years of experience shipping ML systems in production
- Hold yourself and others to a high bar when working with production systems
- Take pride in taking ownership and driving projects to business impact
- Thrive in a collaborative environment
- 5+ years of experience in full time software development roles
- Experience shipping LLM integrations to user products with high quality
- Experience operating in highly ambiguous environments
- Knowledge about driving a hypothesis from data
Skills Required
- At least 3 years of experience shipping ML systems in production
- Experience developing streaming feature pipelines
- Experience building ML models and deploying them to production
- Ability to work with and modify backend code to integrate ML systems
- High standard for production system quality and reliability
- Ownership mindset and ability to drive projects to business impact
- Thrives in a collaborative environment
- 5+ years of full time software development roles
- Experience shipping LLM integrations to user products with high quality
- Experience operating in highly ambiguous environments
- Knowledge of driving a hypothesis from data
Stripe Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stripe and has not been reviewed or approved by Stripe.
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Healthcare Strength — Healthcare is described as comprehensive, including medical, dental, vision, EAP, and mental‑health support such as therapy sessions; wellness resources are consistently highlighted across materials. Coverage breadth and depth are repeatedly positioned as a core strength.
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Parental & Family Support — Paid parental leave for birthing and non‑birthing parents, fertility benefits, and adoption assistance are emphasized, making family support a standout element. Feedback suggests these programs compare favorably to common tech benchmarks.
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Wellbeing & Lifestyle Benefits — Wellness stipends, gym reimbursement, and onsite meals/snacks (where available) are commonly offered, with flexible lifestyle funds supporting varied needs globally. Education stipends and similar perks further bolster day‑to‑day wellbeing.
Stripe Insights
What We Do
Stripe is a technology company that builds economic infrastructure for the internet. Businesses of every size—from new startups to public companies like Salesforce and Facebook—use the company’s software to accept online payments and run technically sophisticated financial operations in more than 100 countries. Stripe helps new companies get started and grow their revenues, and established businesses accelerate into new markets and launch new business models. Over the long term, Stripe aims to increase the GDP of the internet.
