LOG IN
SIGN UP
Canary Wharfian - Online Investment Banking & Finance Community.
Sign In
or continue with e-mail and password
Forgot password?
Don't have an account?
Join Canary Wharfian
or continue with e-mail and password
By signing up, you agree to our Terms & Conditions and Privacy Policy.

Software Engineer, Machine Learning Infrastructure

ExperiencedNo visa sponsorship
Stripe logo

at Stripe

FinTech

Posted 7 days ago

No clicks

**Software Engineer, Machine Learning Infrastructure** Lean in as a Software Engineer, driving machine learning (ML) infrastructure growth. You'll collaborate cross-functionally to streamline ML pipelines, from data exploration to model serving. Key responsibilities include designing secure, scalable services; facilitating ML engineer productivity; and troubleshooting technical hurdles. Proficient in service-oriented architectures and distributed systems with 2+ years of professional software development experience. Familiarity with production ML platforms a plus. Join us to accelerate the internet's GDP and accelerate your career.

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
United States, Canada

Full Job Description

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companiesfrom the worlds largest enterprises to the most ambitious startupsuse 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 everyones reach while doing the most important work of your career.

About the team

Stripe processes over $1T in payments volume per year, which is roughly 1% of the worlds GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure.

What youll do

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.

Responsibilities

  • 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 Stripes 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.

Who you are

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

Minimum requirements

  • 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

Preferred qualifications

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

Software Engineer, Machine Learning Infrastructure

Compensation

Not specified

City: Not specified

Country: United States, Canada

Stripe logo
FinTech

7 days ago

No clicks

at Stripe

ExperiencedNo visa sponsorship

**Software Engineer, Machine Learning Infrastructure** Lean in as a Software Engineer, driving machine learning (ML) infrastructure growth. You'll collaborate cross-functionally to streamline ML pipelines, from data exploration to model serving. Key responsibilities include designing secure, scalable services; facilitating ML engineer productivity; and troubleshooting technical hurdles. Proficient in service-oriented architectures and distributed systems with 2+ years of professional software development experience. Familiarity with production ML platforms a plus. Join us to accelerate the internet's GDP and accelerate your career.

Full Job Description

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companiesfrom the worlds largest enterprises to the most ambitious startupsuse 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 everyones reach while doing the most important work of your career.

About the team

Stripe processes over $1T in payments volume per year, which is roughly 1% of the worlds GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure.

What youll do

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.

Responsibilities

  • 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 Stripes 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.

Who you are

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

Minimum requirements

  • 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

Preferred qualifications

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