🛠 Tech Stack

💼 About This Role

You'll build and operate ML infrastructure for Plaid's network enablement team, powering trust and fraud insights and bank intelligence products. You'll own feature engineering, model serving, and production pipelines to directly impact partner-facing products. This role combines ML engineering with backend systems to scale network intelligence across thousands of financial institutions.

🎯 What You'll Do

• Embed model inference into product APIs, feature flags, and backend flows
• Design and run experiments to validate product hypotheses
• Build offline training pipelines and production batch scoring for bank intelligence
• Ship and maintain real-time model inference endpoints for partner scoring

📋 Requirements

• Strong software engineering skills with Go or Python
• Production experience with Airflow or Spark for data pipelines
• Experience building real-time scoring and online feature-serving systems
• Experience integrating model outputs into product flows and measuring impact via experiments

✨ Nice to Have

• Experience in fraud, risk, or marketing intelligence domains
• Experience with feature-store products like Tecton or Feast
• Experience optimizing inference at scale with Triton or ONNX

🎁 Benefits & Perks

• 🏖️ Flexible PTO
• 💰 Competitive salary and equity
• 🏥 Health, dental, and vision insurance
• 🏢 Hybrid work model with offices in SF, NYC, DC, London, Amsterdam