Staff Machine Learning Engineer - Risk

Company Overview

Breeze is creating an AI-driven infrastructure platform for global commerce, simplifying how businesses sell, receive payments, and operate across different markets. Their offering extends beyond typical payment processing by integrating global payments, artificial intelligence, stablecoins, and a Merchant of Record-like model. Breeze handles complexities such as compliance, risk, fraud detection, chargebacks, reconciliation, and customer service to allow clients to focus on their products.

Supported by notable investors including Sequoia Capital, Multicoin Capital, and The Chainsmokers, Breeze is a well-funded and fast-growing company with a long-term vision and opportunities for impactful contributions from new team members.

Position Summary

The Staff Machine Learning Engineer for Risk will lead the development and advancement of the machine learning platform focused on payment risk detection. This role involves building robust feature engineering, model creation, deployment, monitoring, and ongoing refinement. As payment risk models are central to the business, you will be responsible for their full lifecycle and production health, reporting directly to the CTO.

Key Responsibilities

• Design and implement machine learning infrastructure targeting payment risk identification, leveraging Databricks alongside software and data engineering teams.
• Organize and enhance the ML workflow environment, managing feature pipelines, version control, job scheduling, and system monitoring.
• Develop and deploy models beyond prototypes, managing training pipelines, scheduling retraining, drift analysis, and operational deployment.
• Create dependable, automated, and reproducible end-to-end ML processes.
• Define and uphold technical guidelines and architecture for ML development and delivery within the risk team.
• Ensure continuous operational excellence of production models, including handling low-latency inference, monitoring systems, and incident management.
• Contribute to shaping the future direction of risk management and ML integration at Breeze.

Candidate Profile

• Over 8 years experience in machine learning engineering with ownership of production systems rather than solely research or modeling work.
• Demonstrated history building ML systems related to risk or fraud, preferably within payments or fintech sectors.
• Knowledge of real-time payment risk systems, emphasizing low-latency model inference, monitoring solutions, and managing incident response.
• Strong collaboration skills bridging software and data engineering disciplines.
• Readiness to serve as the lead technical expert within a small team, providing cross-functional leadership and strategic direction.
• Ability to work effectively in dynamic, fast-moving environments lacking established protocols.
• A proactive builder who prioritizes taking action and delivering results.
• Keen on employing AI and automation to optimize and innovate existing workflows.
• Hands-on approach to detailed technical tasks regardless of seniority level.

Preferred Qualifications

• Familiarity with payments-specific risk indicators like chargebacks, dispute networks, and tokenization contexts.
• Experience crafting ML platform standards and operational frameworks in scaling organizations.
• Background in early-stage or rapidly growing startup environments.

Why Work at Breeze

• Integrate AI deeply into a company that transcends payments to cover compliance, risk, fraud, and more.
• Join a successful yet early-stage firm backed by top investors with strong financial resources.
• Enjoy considerable ownership, lean structure, and direct access to decision makers.
• Work on complex, multidisciplinary challenges at the crossroads of AI, financial infrastructure, and global commerce.
• Collaborate with an ambitious, open-minded, fast-paced, and collaborative team.
• Opportunity to rapidly grow in scope and responsibility as the company expands.

Culture and Working Style

• Deliver initial versions quickly and iteratively improve.
• Engage respectfully yet decisively in debates, committing fully to agreed directions.
• Prioritize customer pain points when making decisions.
• Own problems from start to finish without waiting for assignment.
• Maintain transparency by sharing context and learnings broadly.
• Hold high standards while fostering kindness and humility.
• Focus on impactful outcomes rather than busyness.
• Emphasize AI-driven automation and continuous learning.

Compensation Philosophy

• Compensation is competitive, fair, transparent, and benchmarked against the market.
• Pay factors include experience, skills, location, role scope, and impact rather than negotiation intensity.
• Equity grants provide meaningful ownership in the company’s long-term success.

Benefits and Perks

• Annual health stipend plus corporate insurance coverage.
• 21 days paid time off plus public holidays.
• Equity participation alongside a growing team.
• Provision of a new MacBook Air and other required tools.
• Annual allowances for workspace setup and professional development.
• Monthly reimbursement to support wellness activities.
• Annual global team offsite events with locations including Bali, Singapore, and planned Japan trip.

Work Location and Model

This full-time position requires onsite work from the Singapore office, scheduled for five days per week. The company values close in-person collaboration to foster innovation and team cohesion.

Additional Information

Breeze offers early-stage ownership and agility combined with the backing and stability of established financial support. The role focuses on leveraging AI, payments, and financial technology to build next-generation global commerce infrastructure. Candidates seeking significant ownership, challenging problems, and impactful work with an ambitious team are encouraged to apply.