Stripe
Machine Learning Engineer, Supportability
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Machine Learning Engineer, Supportability
role at
Stripe 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. What you’ll do
As a machine learning engineer in Supportability, you will be responsible for designing, building, training, evaluating, deploying, and owning ML models in production. You will work closely with software engineers, machine learning engineers, product managers, and data scientists to operate Stripe’s ML powered systems, features, and products. You will also have the opportunity to contribute to and influence ML architecture at Stripe and be a part of a larger ML community. Responsibilities
— use a proper list below:
Design state-of-the-art ML models and large scale ML systems for detection and decisioning for Stripe products based on 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 ML-based approaches to achieve key business goals 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 Explore cutting-edge ML techniques and evaluate their potential to solve business problems Identify high-impact opportunities, and drive the long-term ML roadmap through well-scoped high-leverage initiatives Who you are
We are looking for ML Engineers who are passionate about building ML systems that touch the lives of millions. You have experience developing efficient feature pipelines, building and evaluating advanced ML models, and deploying them to production. You are comfortable with ambiguity, love to take initiative, have a bias towards action, and thrive in a collaborative environment. Minimum Requirements
2+ 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 Knowledge of various 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 Hands-on experience in orchestrating complicated data pipelines and efficiently leveraging large-scale datasets Experience rigorously evaluating model performance, including cleaning data, and working with data-generating processes to improve signal and reduce noise in high-noise datasets Proficiency in creatively applying modern machine learning techniques and Generative AI models to solve complex business problems Preferred Requirements
MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics) Experience with DNNs including the latest architectures such as transformers and LLMs Experience working in Java or Ruby codebases Proven track record of building and deploying ML systems that have effectively solved ambiguous business problems Experience with online experimentation such as A/B testing or multi-armed bandits Experience with model calibration In-office expectations
Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in our Bucharest, Romania site have an 80% in-office expectation, and those in Stripe Delivery Center roles in Mexico City, Mexico and Bengaluru, India work 100% from the office. Some teams have greater in-office attendance requirements, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible. Pay and benefits
The annual US base salary range for this role is $180,000 - $318,000. For sales roles, the range provided is the role’s On Target Earnings (OTE) range. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on factors such as experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process. Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Software Development, Financial Services, and Technology, Information and Internet
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Join to apply for the
Machine Learning Engineer, Supportability
role at
Stripe 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. What you’ll do
As a machine learning engineer in Supportability, you will be responsible for designing, building, training, evaluating, deploying, and owning ML models in production. You will work closely with software engineers, machine learning engineers, product managers, and data scientists to operate Stripe’s ML powered systems, features, and products. You will also have the opportunity to contribute to and influence ML architecture at Stripe and be a part of a larger ML community. Responsibilities
— use a proper list below:
Design state-of-the-art ML models and large scale ML systems for detection and decisioning for Stripe products based on 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 ML-based approaches to achieve key business goals 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 Explore cutting-edge ML techniques and evaluate their potential to solve business problems Identify high-impact opportunities, and drive the long-term ML roadmap through well-scoped high-leverage initiatives Who you are
We are looking for ML Engineers who are passionate about building ML systems that touch the lives of millions. You have experience developing efficient feature pipelines, building and evaluating advanced ML models, and deploying them to production. You are comfortable with ambiguity, love to take initiative, have a bias towards action, and thrive in a collaborative environment. Minimum Requirements
2+ 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 Knowledge of various 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 Hands-on experience in orchestrating complicated data pipelines and efficiently leveraging large-scale datasets Experience rigorously evaluating model performance, including cleaning data, and working with data-generating processes to improve signal and reduce noise in high-noise datasets Proficiency in creatively applying modern machine learning techniques and Generative AI models to solve complex business problems Preferred Requirements
MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics) Experience with DNNs including the latest architectures such as transformers and LLMs Experience working in Java or Ruby codebases Proven track record of building and deploying ML systems that have effectively solved ambiguous business problems Experience with online experimentation such as A/B testing or multi-armed bandits Experience with model calibration In-office expectations
Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in our Bucharest, Romania site have an 80% in-office expectation, and those in Stripe Delivery Center roles in Mexico City, Mexico and Bengaluru, India work 100% from the office. Some teams have greater in-office attendance requirements, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible. Pay and benefits
The annual US base salary range for this role is $180,000 - $318,000. For sales roles, the range provided is the role’s On Target Earnings (OTE) range. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on factors such as experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process. Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Software Development, Financial Services, and Technology, Information and Internet
#J-18808-Ljbffr