Lead Machine Learning Engineer
OpenTeamsFull Time
Senior (5 to 8 years)
The ideal candidate has experience as a Data Engineer in leading Fintech startups or fast-growing tech companies. They should possess strong fundamentals in data modeling for feature generation and real-world experience with feature stores, either in-house or vendor-based. Proficiency in cloud-native applications such as Google Cloud, AWS, or Azure is required, along with a curiosity for Machine Learning and understanding of data structures, pipelines, and big data processing for real-time consumption. Experience with Python, SQL, Apache Beam, and Polars is also essential.
The Senior Machine Learning Data Engineer will build and integrate data pipelines for ingesting, processing, and serving features in real-time. They will support data models for critical FinCrime products, own the development of the Feature Store, and expand feature engineering capabilities. Responsibilities include enhancing monitoring capabilities with new data alerts, analyzing large datasets using SQL, Apache Beam, and Polars to surface features, and helping to build AI-powered automation tools. The role also involves maintaining and improving existing codebases, expanding internal Feature Store and ML libraries, and proposing improvements across the company.
Cryptocurrency payment solutions and services
MoonPay provides cryptocurrency payment solutions that allow users to easily buy and sell digital assets. The platform operates globally and caters to individual investors, businesses, and developers. Users can make transactions through MoonPay, which charges fees for each purchase or sale. To enhance security, MoonPay also includes services like fraud prevention and compliance support. A key aspect that sets MoonPay apart from its competitors is its commitment to sustainability; it operates as a fully remote and paperless organization and aims to achieve carbon neutrality by 2030 by offsetting emissions and investing in eco-friendly initiatives.