Senior Machine Learning Engineer
Position Summary & Responsibilities
About Attain
Built for consumers and companies, alike.
Klover's engineering team powers one of the fastest-growing fintech platforms in the U.S., supporting over one million active users each month. Our systems process and move more than $1.5 billion annually, enabling real-time access to financial tools, rewards, and services that help people improve their day-to-day lives.
As part of this team, you'll help design, build, and scale the systems that underpin Klover's core products and platform. You'll work on high-impact, production-grade systems that prioritize reliability, security, and performance, and that integrate with a broad ecosystem of internal and external services. The work you do will directly shape how users interact with Klover's products, access their money, and experience transparent, low-fee financial services.
Klover engineers collaborate closely with colleagues across backend, frontend, data science, and product teams to deliver scalable, high-quality solutions for a rapidly growing user base. You'll have the opportunity to work with modern technologies and architectures while helping define and evolve the next generation of inclusive, data-powered financial products—building systems and interfaces that emphasize reliability, privacy, and performance at scale.
About the role
Attain is seeking a Senior Machine Learning Engineer to own our production ML systems and build out the MLOps platform infrastructure that powers our suite of B2C financial services. This role will be highly hands-on and infrastructure-first, focused on designing, building, and operating the pipelines, platforms, and tooling that take models from experiment to reliable production service across our app portfolio—and on keeping those systems healthy, performant, and cost-effective once they're live.
You will work on the systems and infrastructure behind our high-impact predictive models, including the pipelines, feature infrastructure, model-serving, CI/CD, and observability that keep them reproducible, automated, monitored, and fast in production. Day to day, this means building the platform and automation that let us move fast without sacrificing performance—streamlining retraining and rollouts, tuning systems for speed and efficiency, and building the metrics and alerting that give us confidence to ship—while enabling data scientists to deploy and iterate on mo
Key Role Competencies & Evaluation Highlights
Evaluating your mastery of data privacy compliance, consumer behavior analytics, and scaling data-driven loyalty or reward ecosystems.
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