Staff Machine Learning Engineer

February 22

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Referral Rock

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Referral Rock is a referral program software that enables businesses to automate customer acquisition by providing easy-to-implement referral systems. It helps companies launch tailored referral programs quickly, without the need for extensive technical knowledge. With features such as reward management, real-time tracking, and seamless integration with various platforms, Referral Rock allows businesses to leverage their existing customer base to generate new referrals and enhance brand awareness. The platform supports diverse use cases, including customer referral programs, affiliate marketing, and brand ambassador initiatives, ensuring a personalized experience for all participants.

SaaS • Small Business Marketing • Referral Marketing • Customer Referral • Customer Loyalty

11 - 50 employees

Founded 2017

🤝 B2B

🛍️ eCommerce

📋 Description

• We are hiring a Staff Machine Learning Engineer to revolutionize how we optimize our operations using ML and GenAI. • This is a unique opportunity to apply the latest advances in ML and GenAI to real-world problems that directly impact millions of users and the future of digital finance. • Our AI teams are dedicated to building intelligent systems that protect our platform while ensuring a seamless experience for legitimate users. • We are transforming traditional tasks such as manual document review and risk assessment into an automated, scalable system powered by state-of-the-art machine learning. • Design and implement multi-modal ML models that can understand and extract information from various document types (IDs, proof of address, etc.) • Fine tune LLMs for automated document processing and risk assessment. • Design model for ascertaining user onboarding risk and triggering Know-Your-Customer and Enhance Due Diligence models. • Create real-time ML pipelines that can detect and prevent risks before they materialize • Work with experts to translate their domain knowledge into ML features and models • Build explainable ML systems that can justify their risk assessments • Collaborate with platform teams to deploy models at scale with high availability and low latency

🎯 Requirements

• 8+ years of industry experience in Machine Learning (or PhD+5) • MS in Machine Learning, Computer Science, other technical field (PhD preferred) • 10x developer with ability to leverage auto-code generation techniques for ML and scalable distributed applications. • Strong foundation in modern ML techniques (DNNs, transformers, LLMs, classification) • Experience building and deploying production ML systems at scale. • Ability to balance ML model complexity with production requirements • Strong communication skills to work effectively with domain experts • Background in fraud detection or risk modeling • Familiarity with regulatory requirements in financial services • Knowledge of crypto/blockchain technology