Lead Platform Machine Learning Engineer - MoneyLion

Gen Digital Inc.•New York, NY

About The Position

Engine by Gen is a leader in financial technology powering the next generation of personalized products and content, with a top consumer finance super app, a premier embedded finance platform for enterprise businesses and a world-class media arm. Engine by Gen's mission is to give everyone the power to make their best financial decisions. We pride ourselves on serving the many, not the few; providing confidence through guidance, choice, personalization; and shortening the distance to an informed action. In our go-to money app for consumers, we deliver curated content on finance and related topics, through a tailored feed that engages people to learn and share. People take control of their finances with our innovative financial products and marketplace - including our full-fledged suite of features to save, borrow, spend, and invest - seamlessly bringing together the best offers and content from Engine by Gen and our 1,100+ Enterprise Partner network, together in one experience. Engine by Gen's enterprise technology provides the definitive search engine and marketplace for financial products, enabling any company to add embedded finance to their business, with advanced AI-backed data and tools through our platform and API. Engine by Gen connects millions of people with the financial products and content they need, when and where they need it.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
7+ years of experience in software engineering, platform engineering, or DevOps/SRE roles.
Strong systems engineering background with production operations experience.
Strong experience with backend or platform services.
Hands-on experience with cloud infrastructure and tooling (e.g., AWS, Docker, Kubernetes, Terraform, CI/CD, monitoring).
Experience operating distributed systems in production.
Strong problem-solving skills and an operations-first mindset.
Ability to thrive in a fast-paced, high-tech environment and manage complex problems.

Nice To Haves

Experience with machine learning infrastructure, model serving, or data platforms is a strong plus.

Responsibilities

Design, build, and maintain infrastructure supporting ML training, deployment, and inference workloads.
Own and improve CI/CD, infrastructure-as-code, observability, and operational tooling for ML systems.
Operate and evolve production systems with a strong focus on reliability, performance, and cost efficiency.
Build and maintain Kubernetes- and cloud-based services that support model execution and data workflows.
Partner with data scientists and engineers to support model deployment and operational needs.
Improve developer workflows through automation, tooling, and platform abstractions.
Participate in on-call and operational ownership for platform components.