Staff Machine Learning Software Engineer
Join the MEGA team as a Staff Machine Learning Software Engineer, designing and building scalable ML systems and infrastructure to support advanced robotics research.
At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets.
We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support.
Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid.
Backed by Sequoia Capital, Multicoin Capital, and The Chainsmokers, Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build.
We are hiring a Staff Machine Learning Engineer, Risk!
As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO.
You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team.
We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain.
What You'll Do
Nice to Have
Our Compensation Philosophy!
We believe compensation should be fair, competitive, consistent, and transparent. We benchmark compensation against the market and establish thoughtful bands for each role, with compensation reflecting experience, skills, location, role scope, and expected impact. We don't believe pay should primarily depend on how aggressively someone negotiates. Eligible employees receive meaningful equity, so the people building Breeze can participate in the long-term value they help create.
Benefits & Perks
Benefits, allowances, and reimbursements are subject to applicable eligibility requirements, taxes, and statutory contributions. Benefits are not contractual and may be amended from time to time.
Why Join Breeze
In-Office Expectations
Employees based in our New York City, NY office follow a hybrid work model and are expected to work from the office three days per week. Employees based in our Singapore office are expected to work on-site five days per week.
In-office expectations may vary slightly depending on role, team, and business needs. Certain roles that require closer cross-functional collaboration or operational support may have additional requirements, which will be discussed during the interview process.
Our approach is designed to support meaningful in-person collaboration, team building, and real-time decision-making while providing flexibility where applicable. We believe this structure enables strong execution, close collaboration, and effective teamwork across our global offices.
Come Build With Us!
We offer a rare combination: the ownership and speed of an early-stage company with the traction, backing, and financial foundations of a successful business.
We're building at the convergence of AI, payments, stablecoins, financial infrastructure, and global commerce. The opportunity is much bigger than building another payment processor.
We're building the intelligent infrastructure layer for global commerce, and there's still an enormous amount left to build.
If you want meaningful ownership, hard problems, exceptional teammates, and the opportunity to help define what comes next, we'd love to hear from you!
Join the MEGA team as a Staff Machine Learning Software Engineer, designing and building scalable ML systems and infrastructure to support advanced robotics research.
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