Machine Learning Engineer, Radar på Stripe i Seattle
Stripe · Seattle
Machine Learning Engineer, Radar
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 ...
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
The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns
10+ real-time deep learning models that must constantly evolve to stay ahead of fraudsters. Each ML improvement translates
directly into dollar impact for Stripe and its users.
The team's models also power the Radar product suite that tens of thousands of businesses use to screen payments and manage fraud.
Radar is growing fast, and the team is actively building new products like defenses against AI token theft, free trial abuse, and
programmatic attacks.
WHAT YOU’LL DO
In this role, you will own ML work across the full lifecycle: researching new fraud patterns, building and deploying models, and
sharing results directly with top Stripe customers. You will have opportunities to optimize Stripe’s most intensive ML models, and
opportunities to ship 0-to-1 products from scratch.
RESPONSIBILITIES
Build, train, evaluate, and deploy ML models that detect fraud across Stripe’s global payments network
Research emerging fraud patterns like token theft and develop ML solutions to address them
Apply advances in deep learning to improve model quality and detection rates at scale
Co-build new fraud and abuse products directly with top users
WHO YOU ARE
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you
are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
MINIMUM REQUIREMENTS
6+ years of industry experience training, evaluating, and deploying ML models in a production environment
Proficiency in Python and common data and ML frameworks like SQL, Spark, and PyTorch
Strong knowledge of production ML systems; and data analysis, statistics, and experiment design fundamentals
Active interest in the latest ML developments, and how they can be leveraged to solve business problems
PREFERRED QUALIFICATIONS
Experience building and optimizing real-time, low-latency ML infrastructure at scale
Strong software engineering skills and ability to design ML solutions through entire product stack
Experience applying ML to fraud detection, risk modeling, or a closely related domain
Experience designing ML products used by millions of users
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
Stripe processes over $1.9T in payments volume per year, which is roughly 1.6% of the world's GDP, for millions of customers from
startups to enterprises. The tremendous amount of data makes Stripe one of the best places to do machine learning. While being an
integral part of almost every product line at Stripe (e.g., Payments, Radar, Capital, Billing, etc.), we have lots of exciting
opportunities to innovate in ML Platform at Stripe.
The ML Platform team builds the platforms and services that enable ML engineers and data scientists across Stripe to take data and
build features and models from prototype to production—reliably, at low latency, and at scale. Our scope spans ML training
infrastructure, model serving and deployment, feature computation and online serving, observability and monitoring, and agentic AI
capabilities. We work closely with product teams, data scientists, and platform infrastructure teams to build powerful, flexible,
and user-friendly systems that substantially increase ML velocity across the company.
WHAT YOU'LL DO
You'll serve as a technical lead across the ML Platform space and a key contributor to the evolution of the platforms that power
Stripe's ML-driven products. As a Staff Engineer, you'll make decisions with a large impact on Stripe. You'll influence our
investments and strategy while making our systems more reliable, secure, and a delight to use. You'll work cross-functionally with
other technical staff, data science, product, and senior leadership to increase the impact of ML at Stripe.
You'll help define the long-term strategy and lead the technical direction for the next generation of ML infrastructure that
powers Stripe's ML-driven products.
RESPONSIBILITIES
* Take ownership of end-to-end architecture and system design for large, complex projects across ML Platform.
* Define technical direction for highly ambiguous projects, transforming complex user needs into long-lasting platform strategy.
* Design system architectures for the most challenging ML Platform problems in one or more areas, including AI and ML workflow
orchestration, scalable CPU and GPU compute infrastructure, model training, LLM fine-tuning, low-latency model inference,
large-scale feature stores, real-time monitoring, and LLM and agent orchestration.
* Turn high-leverage ideas into tangible, robust solutions that shape platform and product roadmap, combining technical
excellence with creative problem-solving.
* Scope and lead large projects with significant business impact, driving them from requirements through design, implementation,
and production operation.
* Work with ML engineers, data scientists, and product teams directly to translate their needs into functional requirements and
scalable technical solutions.
* Arbitrate critical decisions that balance competing priorities while meeting latency, reliability, cost, and security
constraints.
* Serve as a key engineering representative, engaging senior leaders across Stripe and advising the leadership team on key
technical considerations related to the end-to-end ML lifecycle.
* Drive cross-team technical initiatives that improve ML development velocity and MLOps maturity across the company.
* Mentor and grow other engineers. Serve as a role model for designing, implementing, and operating great software systems.
WHO YOU ARE
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you
are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
MINIMUM REQUIREMENTS
* 10+ years of professional software development experience, or equivalent domain expertise, with a solid background in
service-oriented architecture and large-scale distributed systems.
* Track record of serving as a technical lead, with the ability to provide technical direction, lead multi-team initiatives, and
mentor team members.
* Experience building and operating production ML platform in one or more areas such as model training, model serving,
orchestration, or ML data systems, with requirements for performance, reliability, scalability, and cost efficiency.
* Strong product instincts and a deep understanding of the business context in which you operate.
* Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical
stakeholders.
* Demonstrated ability to work cross-functionally, collaborating effectively with ML engineers, data scientists, software
engineers, product managers, and business stakeholders.
* The ability to thrive on a high level of autonomy and responsibility, and comfort operating in ambiguous environments.
* Hands-on experience using AI tools to accelerate how you work.
PREFERRED QUALIFICATIONS
* Experience building large-scale ML training, serving, or data infrastructure for machine learning use cases, such as
distributed training, model inference, feature stores, real-time feature computation, and model registries.
* Experience with distributed ML training systems, accelerator-backed compute, training data pipelines, experiment tracking, and
model evaluation.
* Experience rapidly developing prototypes and iterating based on user feedback.
* Experience training and shipping machine learning models to production to solve critical business problems.
* Familiarity with LLMs, LLM application frameworks, and agentic AI patterns (e.g., tool use, multi-agent orchestration,
retrieval-augmented generation).
* Familiarity with cloud services (e.g., AWS) and cloud-based AI and ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI).
* Ability to synthesize ideas across the organization while setting a compelling technical vision.
* Comfortable working with geographically distributed teams.
* Passion for side projects, open source, or self-driven technical initiatives.
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
Stripe processes over $1.9T in payments volume per year, which is roughly 1.6% of the world's GDP, for millions of customers from
startups to enterprises. The tremendous amount of data makes Stripe one of the best places to do machine learning. While being an
integral part of almost every product line at Stripe (e.g., Payments, Radar, Capital, Billing, etc.), we have lots of exciting
opportunities to innovate in ML Platform at Stripe.
The ML Platform team builds the platforms and services that enable ML engineers and data scientists across Stripe to take data and
build features and models from prototype to production—reliably, at low latency, and at scale. Our scope spans ML training
infrastructure, model serving and deployment, feature computation and online serving, observability and monitoring, and agentic AI
capabilities. We work closely with product teams, data scientists, and platform infrastructure teams to build powerful, flexible,
and user-friendly systems that substantially increase ML velocity across the company.
WHAT YOU'LL DO
You'll serve as a technical lead across the ML Platform space and a key contributor to the evolution of the platforms that power
Stripe's ML-driven products. As a Staff Engineer, you'll make decisions with a large impact on Stripe. You'll influence our
investments and strategy while making our systems more reliable, secure, and a delight to use. You'll work cross-functionally with
other technical staff, data science, product, and senior leadership to increase the impact of ML at Stripe.
You'll help define the long-term strategy and lead the technical direction for the next generation of ML infrastructure that
powers Stripe's ML-driven products.
RESPONSIBILITIES
* Take ownership of end-to-end architecture and system design for large, complex projects across ML Platform.
* Define technical direction for highly ambiguous projects, transforming complex user needs into long-lasting platform strategy.
* Design system architectures for the most challenging ML Platform problems in one or more areas, including AI and ML workflow
orchestration, scalable CPU and GPU compute infrastructure, model training, LLM fine-tuning, low-latency model inference,
large-scale feature stores, real-time monitoring, and LLM and agent orchestration.
* Turn high-leverage ideas into tangible, robust solutions that shape platform and product roadmap, combining technical
excellence with creative problem-solving.
* Scope and lead large projects with significant business impact, driving them from requirements through design, implementation,
and production operation.
* Work with ML engineers, data scientists, and product teams directly to translate their needs into functional requirements and
scalable technical solutions.
* Arbitrate critical decisions that balance competing priorities while meeting latency, reliability, cost, and security
constraints.
* Serve as a key engineering representative, engaging senior leaders across Stripe and advising the leadership team on key
technical considerations related to the end-to-end ML lifecycle.
* Drive cross-team technical initiatives that improve ML development velocity and MLOps maturity across the company.
* Mentor and grow other engineers. Serve as a role model for designing, implementing, and operating great software systems.
WHO YOU ARE
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you
are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
MINIMUM REQUIREMENTS
* 10+ years of professional software development experience, or equivalent domain expertise, with a solid background in
service-oriented architecture and large-scale distributed systems.
* Track record of serving as a technical lead, with the ability to provide technical direction, lead multi-team initiatives, and
mentor team members.
* Experience building and operating production ML platform in one or more areas such as model training, model serving,
orchestration, or ML data systems, with requirements for performance, reliability, scalability, and cost efficiency.
* Strong product instincts and a deep understanding of the business context in which you operate.
* Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical
stakeholders.
* Demonstrated ability to work cross-functionally, collaborating effectively with ML engineers, data scientists, software
engineers, product managers, and business stakeholders.
* The ability to thrive on a high level of autonomy and responsibility, and comfort operating in ambiguous environments.
* Hands-on experience using AI tools to accelerate how you work.
PREFERRED QUALIFICATIONS
* Experience building large-scale ML training, serving, or data infrastructure for machine learning use cases, such as
distributed training, model inference, feature stores, real-time feature computation, and model registries.
* Experience with distributed ML training systems, accelerator-backed compute, training data pipelines, experiment tracking, and
model evaluation.
* Experience rapidly developing prototypes and iterating based on user feedback.
* Experience training and shipping machine learning models to production to solve critical business problems.
* Familiarity with LLMs, LLM application frameworks, and agentic AI patterns (e.g., tool use, multi-agent orchestration,
retrieval-augmented generation).
* Familiarity with cloud services (e.g., AWS) and cloud-based AI and ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI).
* Ability to synthesize ideas across the organization while setting a compelling technical vision.
* Comfortable working with geographically distributed teams.
* Passion for side projects, open source, or self-driven technical initiatives.
Vi söker nu flera ingenjörer till en växande Data & AI-avdelning inom försvarssektorn. Här blir du en del av utvecklingen av avancerade Data Fusion-produkter som utgör en central komponent i moderna ledningssystem. Nu tas nästa steg i utvecklingen där mer datadrivna AI-funktioner integreras i systemen.
För att möjliggöra detta söker vi dig som vill vara med och utveckla framtidens intelligenta beslutsstöd inom någon av följande områden:
Data Engineer / Data Scientist – Core Data Platform
I denna roll arbetar du nära verksamhetens kärna med att utveckla och vidareutveckla organisationens centrala datamodell.
Du kommer exempelvis att:
Arbeta med utveckling och strukturering av data i en central dataplattform / data lake
Transformera och kvalitetssäkra rådata till användbara dataprodukter
Möjliggöra datatillgång för andra utvecklingsteam
Bidra genom hela data science-processen – från insamling till analys och implementation
Bygga skalbara lösningar i moderna molnmiljöer
AI Engineer – Machine Learning & LLM
I denna roll blir du en del av ett dedikerat AI-team med fokus på nästa generations intelligenta system.
Du kommer exempelvis att:
Arbeta med utveckling och tillämpning av Machine Learning-modeller
Utforska och implementera lösningar baserade på LLM-teknologi
Bygga och produktionssätta AI-lösningar i molnbaserade miljöer
Arbeta nära data engineers för att operationalisera AI på strukturerad data
Rollen är placerad i Järfälla, Stockholm.
Att vara konsult på Nexer Tech Talent
Nexer Tech Talent är specialister på att ge techtalanger den ultimata starten på arbetslivet. För denna roll kommer du att bli anställd av Nexer Tech Talent men arbeta hos vår kund.
Du kommer att coachas av en konsultchef på Nexer Tech Talent. Som konsult hos oss blir du väl omhändertagen och bjuds ofta in på gemensamma aktiviteter så som föreläsningar, afterwork och lunchträffar. Efter framgångsrikt genomförande av konsultuppdraget är intentionen att du erbjuds en anställning hos vår kund.
Vi söker dig som:
Har minst 1–3 års arbetslivserfarenhet inom Data, AI eller närliggande område
Erfarenhet av Python och/eller C++
Erfarenhet av cloudplattformar såsom AWS och Azure
Erfarenhet av systemutveckling ses som meriterande
Ansökan
Låter detta som något för dig? Vi arbetar löpande med rekryteringen, så skicka in din ansökan snarast möjligt. Om du har du frågor eller funderingar är du välkommen att kontakta Tech Recruiter Molly Rytter på molly.rytter@nexergroup.com.
Befattningen kräver att du genomgår och godkänns enligt vid var tid gällande bestämmelser för säkerhetsskydd. För befattningar där Saab har krav på säkerhetsklassinplacering kan, i förekommande fall, medföra krav på visst medborgarskap.
Vi ser fram emot att höra från dig!
Om Nexer Tech Talent Nexer Tech Talent är en del av Nexer Group med väletablerade ramavtal, långsiktiga samarbete och några av Sveriges mest välkända och betydelsefulla kunder. Tillsammans är vi över 2500 medarbetare i 16 länder som i mer än 35 år hjälpt våra kunder ligga steget före både strategiskt, teknologiskt och kommunikativt. Läs mer om oss här.
