The Role

Are you a highly skilled ML engineer looking to own the lifeblood of a growing startup? In this role, you'll be responsible for Alt's core card pricing model, the critical engine that automates our cash advance decisions, powers our risk assessment framework and enables card valuations that collectors rely on for market research. You'll apply your expertise in both data science and ML operations to improve model accuracy and optimize our infrastructure for scalability and cost-effectiveness.

What you'll do here

• Optimize our pricing model to significantly reduce infrastructure costs while maintaining and improving its accuracy especially for high value cards.
• Iterate on our underwriting model to maximize cash advance disbursements while maintaining target risk thresholds and default rates.
• Lead the full ML lifecycle from model training and feature generation to production deployment and monitoring.
• Collaborate closely with our Expert Pricers to become a domain expert in the trading card market and inform model improvements.
• Design and execute experiments and backtesting to discover and validate new features that improve the model's predictive power.
• Own the model's AWS infrastructure, writing code for our pricing API to ensure the model can serve at scale and with low latency.

This is a perfect fit if you...

• Are passionate about trading cards or a similar alternative asset class, with a desire to go deep on the domain.
• Are a hands-on individual contributor who thrives in a zero-to-one startup environment.
• Want to own a business-critical system and have the opportunity to build a team around you.
• Are pragmatic and prefer to build a solution to a problem, not replace an entire system just for the sake of it.
• Are highly curious with a strong desire to learn.

What you bring to the table

• 10+ years of total engineering experience with at least 4-5 years of direct machine learning experience.
• Expertise in Python with hands-on experience using libraries such as scikit-learn, XGBoost, and pandas.
• A strong foundation in ML Ops and infrastructure, with experience deploying models on AWS using tools like ECS and Docker.
• Experience in data orchestration using Airflow for model training and batch jobs.
• A demonstrated ability to improve model accuracy through feature generation and experimentation.
• Experience working with Random Forest, ensemble methods or pricing/underwriting models in a similar marketplace environment

What You’ll Get From Us

• A seat at the table to help shape the future of Alt and the alternative asset space

• Autonomy and ownership on projects that matter

• $100/month work-from-home stipend

• $200/month wellness stipend

• WeWork office stipend

• 401(k) retirement benefits

• Flexible vacation policy

• Generous paid parental leave

• Competitive healthcare benefits, including HSA, for you and your dependent(s)

Base salary range: $240,000–$270,000, plus equity. Offers may vary based on experience, location, and other factors.