XGBoost Jobs

Growth Platform at Stripe builds machine learning systems to help businesses discover and utilize Stripe products. These recommendations are integrated across various platforms including the Dashboard, email, onboarding, documentation, and AI agent interfaces. The team combines business understanding with models to determine the most useful recommendations, optimal timing, and effective learning from outcomes. Their work encompasses recommendation and ranking models, contextual bandits, agent-based recommendations, and the underlying data and evaluation systems, aiming to drive business growth through relevant product adoption while maintaining a positive user experience.

Stripe is seeking a Machine Learning Engineer for its Link Fraud and Auth team. This role involves building and operating models and risk decisioning systems to protect Link while enabling legitimate payments. You will manage the full machine learning lifecycle, from analyzing fraud patterns and identifying opportunities to developing, deploying, monitoring, and improving models in production. Your work will directly impact Link's fraud performance, authorization rates, and expansion into new products and payment experiences, contributing to Stripe's mission to increase the GDP of the internet.

Financial Connections is Stripe's open banking platform, enabling businesses to securely access consumer-permissioned financial data. Our platform connects to thousands of financial institutions, powering use cases from account verification to risk assessment to personal financial management. Across the Financial Connections Engineering org, we focus on delivering high-quality, enriched bank data at scale — building the ML systems that transform raw financial data into actionable signals for both internal Stripe teams and external merchants. Our ML work spans transaction categorization, risk scoring, data enrichment, and the development of intelligent systems that improve data quality across our network. We operate at the intersection of fintech infrastructure and applied machine learning, solving problems that directly impact Stripe's ability to serve millions of businesses and consumers.

The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns over 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. 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.

As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems. You will build end-to-end pipelines that extract signals, train custom models per merchant, and serve predictions at production scale with low latency. You will work on an automated machine learning ecosystem that dynamically recalibrates models based on streaming global telemetry data.

$140k - $190k

Plaid is seeking a Senior Machine Learning Engineer to join their Fraud Data team. This role will focus on developing and deploying machine learning systems to enhance Plaid's fraud detection products. You will work across the full data science and machine learning lifecycle, from identifying new signals and experimenting with models to deploying and optimizing them in production. The goal is to continuously learn from real-world performance and customer feedback to protect customers from evolving fraud threats. You will lead projects from initial experiments through model deployment and ongoing improvement, identifying predictive patterns in Plaid's network data.

$229k - $315k

Cinder is seeking an AI Engineer to join their fast-moving team, backed by Accel and Y Combinator. This role is crucial for building the ML systems that enhance Cinder's speed, efficiency, and accuracy. You will transform vast amounts of customer decision data into production models that directly impact customer outcomes. The ideal candidate is a builder who has successfully taken models from raw data to production at scale, possesses strong judgment in selecting the most efficient and reliable model for a given task, and has a deep understanding of both ML methods and LLMs. This position requires a keen focus on precision-recall tradeoffs, class imbalance, and serving latency, alongside model architecture.

$220k - $260k

Figma is seeking a versatile and experienced Machine Learning / AI Engineer to join our growing AI team, working at the intersection of applied machine learning, infrastructure, and product innovation. Whether you’re building intelligent search systems, crafting scalable data pipelines, or enhancing AI-powered creativity tools, your work will drive user productivity, shape new product experiences, and advance the state of AI at Figma. You’ll collaborate closely with engineers, researchers, designers, and product managers across multiple teams to deliver high-quality ML-driven features and infrastructure. This is a high-impact, cross-functional role where you’ll shape both foundational systems and user-facing capabilities. This is a full time role that can be held from one of our US hubs or remotely in the United States.

$153k - $376k

Faire is a technology wholesale platform dedicated to empowering independent retailers globally. We leverage machine learning (ML) and data insights to help local businesses compete effectively. Our Data Science team develops and maintains a variety of algorithms and models that drive our marketplace, focusing on solutions for notification and recommender systems, advertising attribution, and Lifetime Value (LTV) predictions. As a Data Scientist on the Retailer team, you will tackle diverse challenges, including optimizing logistics, underwriting creditworthiness, enhancing search engine optimization, personalizing landing pages, and predicting retailer lifetime value. You will collaborate with data scientists, engineers, and product managers to unlock value from our extensive marketplace data.

$211k - $291k

We are looking for an experienced and motivated senior engineer with expertise in backend services and ML infrastructure. In this role, you will help integrate cutting-edge AI models into services and toolkits for researchers and developers. You will work closely with research scientists and other engineers to build new capabilities into the Hume platform. You will have the opportunity to take part in a wide range of engineering initiatives across backend applications, cloud infrastructure, and the ML lifecycle, including evaluation and deployment at scale.

$180k - $250k