The Role

We're looking for a product-minded Machine Learning Engineer to pioneer the engineering of intelligent resilience systems at Fusion. This role will focus on designing, building, deploying, and operating production-grade machine learning systems-including reinforcement learning and optimization-driven intelligence-to power the next generation of resilience capabilities.

You will architect and deliver scalable ML systems that unify resilience data from some of the world's largest and most systemically important organizations. This includes building robust model pipelines, integrating simulation and optimization engines into production services, and establishing strong ML Ops and AI Ops practices to ensure reliability, performance, and governance at scale.

This is a high-ownership role for someone who thrives at the intersection of software engineering and machine learning-someone who wants to build durable AI/ML infrastructure, ship intelligent product features, and solve complex real-world operational resilience challenges.

Key Responsibilities

• Design, build, deploy, and maintain production machine learning systems, including reinforcement learning components and intelligent optimization-driven features.

• Architect scalable ML pipelines for training, validation, deployment, monitoring, and automated retraining.

• Maintain and expand operations for simulation (Monte Carlo, Bayesian Networks) and optimization engines (linear, constraint, CP-SAT) for continued reliable service.

• Own ML Ops and AI Ops practices, including CI/CD for models, automated testing, model validation, performance monitoring, drift detection, observability, and governance frameworks.

• Refactor and harden existing AI systems to improve scalability, latency, cost efficiency, and fault tolerance.

• Build and maintain data pipelines and feature engineering workflows that support reliable and reproducible model training.

• Collaborate closely with product and engineering teams to translate resilience use cases into scalable, maintainable ML-powered product capabilities.

• Contribute to the design of Fusion's ML architecture, infrastructure standards, and long-term intelligent systems roadmap.