MLE – Staff Machine Learning Engineer

Our client, an innovator in the financial services industry, is hiring a Staff Machine Learning Engineer to join their team remotely. The successful candidate will leverage their expertise in data science and ML operations to enhance model accuracy while optimizing infrastructure for both scalability and cost efficiency.

Responsibilities

• Enhance their pricing model to boost accuracy for high-value cards while minimizing infrastructure costs.
• Refine our underwriting model to optimize cash advance disbursements while keeping risk and default rates in check.
• Own the full ML lifecycle, from model training and feature engineering to deployment and monitoring.
• Work closely with pricing experts to gain deep domain knowledge of the trading card market and drive model improvements.
• Plan and run experiments and back tests to identify and validate features that strengthen predictive performance.
• Manage AWS infrastructure and develop code for our pricing API to ensure scalable, low-latency model delivery.

Skillset

• Minimum of 10 years of engineering experience, including at least four years focused on machine learning.
• Deep expertise in Python, with hands-on experience in libraries such as scikit-learn, XGBoost and pandas.
• Strong ML Ops and infrastructure background, with experience deploying models on AWS using ECS and Docker.
• Skilled in data orchestration and workflow management using Airflow for model training and batch processing.
• Demonstrated success improving model accuracy through feature engineering and experimentation.
• Experience with Random Forest, ensemble methods, or pricing/underwriting models in marketplace or fintech environments.

Benefits

• Salary: Circa. $250k.
• Equity.
• Remote working.
• 401(k) retirement benefits.
• Competitive healthcare package.

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