Machine Learning Engineer (Fintech)

TL;DR

Machine Learning Engineer (Fintech): Designing and deploying production ML models for underwriting and portfolio management within hirify.global Capital with an accent on scalability, reliability, and risk management. Focus on building state-of-the-art systems using PyTorch and TensorFlow to automate financing offers and optimize business performance.

Location: Must be based in or able to work from South San Francisco HQ or New York

Salary: $180,000 - $270,000

Company

hirify.global is a financial infrastructure platform for businesses, processing over $1T in payments volume annually to increase the GDP of the internet.

What you will do

• Design state-of-the-art ML models and large-scale systems for underwriting and portfolio management for hirify.global Capital.
• Experiment and iterate on ML models using PyTorch and TensorFlow to achieve key business goals and drive efficiency.
• Develop automated pipelines for training and evaluating models in both offline and online environments.
• Integrate ML models into production systems ensuring high scalability and reliability.
• Collaborate with software engineers, data scientists, product and risk managers to operate ML-powered systems.
• Research and implement the latest AI/ML developments to transform innovative ideas into productionized solutions.

Requirements

• 5+ years of industry experience building and shipping ML systems in production.
• Proficiency with ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, and Spark.
• Strong knowledge of various ML algorithms, model architectures, and data pipeline orchestration.
• Hands-on experience in designing, training, evaluating, and deploying models at scale.
• Experience collaborating across multi-functional teams, specifically Data Science and Risk Management.
• Must be based in the US (South San Francisco or New York).

Nice to have

• MS/PhD degree in ML/AI or a related field such as math, physics, or statistics.
• Experience in adversarial domains including Lending, Trading, or Fraud.
• Expertise in Deep Learning, including transformers, reinforcement learning, and test-time compute.

Culture & Benefits

• Opportunity to work on financial infrastructure impacting millions of businesses globally.
• Access to massive datasets (petabytes) and a highly scalable ML platform.
• Collaborative environment with a strong, active internal ML community.
• Focus on solving challenging problems with direct and significant business impact.