ApplySarthiMachine Learning Engineer
Stripe
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This role on the market
1,073 open learning roles across 261 companies are on ApplySarthi right now, most of them in Bengaluru (63), Hyderabad (24), Delhi NCR (14).
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What learning roles keep asking for: Machine learning (48%), Python (35%), LLMs (22%), PyTorch (22%), Deep learning (16%), AWS (13%), Generative AI (13%) — counted across their open postings here.
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Stripe has 702 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for learning roles keep coming back to Machine learning, Python, LLMs, PyTorch. Practise those questions before you sit with Stripe.
Questions you are likely to be asked
- Why do you want to join Stripe?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- Tell me about a time the data was messy or wrong. What did you do?
- How would you explain your model's result to someone who is not technical?
- What would you check first if a model's accuracy dropped after going live?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Machine Learning Engineer at Stripe interview free →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. 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 team
Our 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 do
As 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.
Responsibilities
Our 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
Who you are
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
Preferred qualifications
- 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
Match this job to your CV
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Listed on greenhouse · posted 2026-07-10. ApplySarthi collects openings and links to application pages; the role is advertised by Stripe, not by us.