Senior Machine Learning Engineer

• Optimize our pricing models to significantly reduce infrastructure costs while maintaining and improving their accuracy, especially for high-value assets.
• 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 models’ predictive power and coverage.
• Own the models’ AWS infrastructure, writing code for our pricing APIs to ensure the models can serve at scale and with low latency., * Shipped leaner, more accurate pricing models. You’ve cut infrastructure cost meaningfully while improving accuracy, especially on high-value assets.
• Moved underwriting from good to great. You’ve iterated on the underwriting model to increase cash advance disbursements without breaching risk thresholds.
• Earned trust with Expert Pricers. You’re a go-to partner for the pricing team - you understand the domain deeply enough that your model changes reflect real market judgment, not just data.
• Hardened the production path. The pricing APIs are faster, more observable, and easier to reason about, with monitoring in place to catch model drift or degradation before it hits customers.

• 7+ years of engineering experience, with 5+ years building and shipping production ML/AI models.
• Deep proficiency in production-grade Python and SQL, including building custom feature-engineering pipelines (not just off-the-shelf scikit-learn). Think time-decay weighting, leakage-safe k-fold cross-validation, and cascading fallback/imputation logic.
• Experience training and validating gradient-boosted or ensemble estimators against strict accuracy/error tolerances, with segment-specific tuning (e.g., by category or asset type).
• Experience leveraging LLMs, foundation models, and AI dev tools for both internal tooling and user-facing product use cases in production.
• Experience with MLflow or a comparable tool for experiment tracking and model registry/versioning.
• Comfortable owning production model-serving infrastructure on AWS - capacity planning, auto-scaling, and diagnosing memory/timeout failures at scale.
• Experience with CI/CD pipelines, orchestrating production workflows, and IaC for provisioning and modifying cloud infrastructure.
• Pragmatic and focused on delivering value incrementally rather than pursuing perfection.

Nice-to-haves:

• Experience with real-time or low-latency models serving at scale.
• Previous startup experience - you understand and thrive on the pace, adaptability, and ownership required in a fast-moving environment.
• Interested in or knowledgeable of trading cards, collectibles, or alternative asset markets.

Pulled from the full job description Work from home stipend Paid parental leave Parental leave 401(k) Health insurance Health savings account

Full job description

Alt is unlocking the value of alternative assets, starting with the $5 B trading-card market. We let collectors buy, sell, vault, and finance their cards in one place and we are backed by leaders at Stripe, Coinbase, Seven Seven Six, and pro athletes like Tom Brady and Giannis Antetokounmpo. Our next frontier is real-time pricing at scale-the Alt Value that powers every trade, loan, and product on the platform., * 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)