Operations jobs in United States

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.

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.

You will work closely with machine learning engineers, data scientists, and product engineering teams to enable seamless end‑to‑end experience in building solutions across data, analytics, and AI/ML platforms. You will build the next generation of ML Infra services and major new capabilities that substantially improve ML development velocity and MLOps maturity across the company.

• Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions.
• Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems.
• Working directly with product teams and ML engineers to improve their day‑to‑day productivity.
• Taking ownership of and finding solutions for technical and product challenges by working with a diverse set of systems, processes, and technologies.

We’re looking for people with a strong background or interest in building successful products or systems; you’re passionate about solving business problems and making impact, you are comfortable in dealing with lots of moving pieces; and you’re comfortable learning new technologies and systems. You are comfortable working with other Stripe teams across the US and Canada.

• 2+ years of professional software development experience with a solid background on service oriented architecture and large-scale distributed systems
• Experience working through the full life cycle of software development, from talking to users, to design and implementation, to testing and deployment, to operations
• Experience working on production ML platforms, MLOps solutions, or building LLM applications
• Experience running operations for high availability, low latency systems
• Experience partnering with other teams to drive business outcomes
• A sense of pragmatism: you know when to aim for the ideal solution and when to adjust course

• Familiarity with the LLMs and LLM Frameworks
• Experience training and shipping machine learning models to production to solve critical business problems

Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in‑person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.

The annual salary range for this role in the primary location is C$135,200 - C$258,000. This range may change if you are hired in another location. For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and specific location. Applicants interested in this role and who are not located in the primary location may request the annual salary range for their location during the interview process.

Specific benefits and details about what compensation is included in the salary range listed above will vary depending on the applicant’s location and can be discussed in more detail during the interview process. Benefits/additional compensation for this role may include: equity, company bonus or sales commissions/bonuses; retirement plans; health benefits; and wellness stipends.

Office locations

Toronto

Team

Machine Learning

Job type

Full time

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