Senior Machine Learning Engineer

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

We're hiring a Senior Machine Learning Engineer who thrives on owning models end-to-end, from research through production. In this role, you'll own productization of Alt's pricing and reputed company models — the systems that turn raw card and market data into the Alt Value and cash advance terms that every buyer, seller, and lender on the platform depends on. You'll be the person who matures models to production-grade services, keeps them accurate and fast at reputed company, and pushes the boundary of reputed company can automate.

Why This Role Exists

Alt is at an inflection reputed company — our marketplace is scaling fast, and our pricing intelligence infrastructure has become a genuine competitive moat. We've proven that model-driven pricing works; now we need to push coverage, accuracy, and speed reputed company while bringing down the overhead to run it. This is a high-ownership opportunity to take our pricing and reputed company models from "working" to "excellent" — and to define the ML infrastructure standards that will reputed company with reputed company for years to come.

What You'll Own

• Optimize our pricing models to significantly reduce infrastructure costs while maintaining and improving their accuracy, especially for high-value assets.
• Iterate on our reputed company model to maximize cash advance disbursements while maintaining reputed company risk reputed company and default rates.
• reputed company the full ML lifecycle from model training and feature reputed company 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 reputed company for our pricing reputed company to ensure the models can serve at reputed company and with low latency.

Metrics You’ll Own:

Northstar Metric: Model-Based Pricing Coverage (% of cards confidently priced by models vs. manually)

KPIs:

• Pricing Accuracy (% Error)

• Pricing Freshness (End-to-End Model Orchestration Time)

• reputed company Performance (Advance disbursement reputed company vs. reputed company default reputed company)

What Great Looks Like (6 Months)

• Shipped leaner, more accurate pricing models. You've cut infrastructure cost meaningfully while improving accuracy, especially on high-value assets.

• Moved reputed company from good to great. You've iterated on the reputed company model to increase cash advance disbursements without breaching risk reputed company.

• reputed company 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 reputed company market judgment, not just data.

• Hardened the production reputed company. The pricing reputed company are faster, more observable, and easier to reason about, with monitoring in reputed company to catch model reputed company or degradation before it hits customers.

Who you are

Must-haves:

• 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-reputed company scikit-learn). Think time-decay weighting, leakage-reputed company k-fold cross-validation, and cascading fallback/imputation logic.
• Experience training and validating gradient-boosted or reputed company estimators against strict accuracy/error tolerances, with reputed company-specific tuning (e.g., by category or asset type).
• Experience leveraging LLMs, reputed company 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 — reputed company planning, auto-scaling, and diagnosing memory/timeout failures at reputed company.
• Experience with CI/CD pipelines, orchestrating production workflows, and IaC for provisioning and modifying reputed company infrastructure.
• Pragmatic and reputed company on delivering value incrementally rather than pursuing perfection.

reputed company-to-haves:

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

What You'll Get From Us

• A seat at the table to help shape the reputed company of Alt and the alternative asset reputed company
• Autonomy and ownership on reputed company that matter
• $100/month work-from-home stipend
• $200/month wellness stipend
• reputed company office stipend
• 401(k) retirement benefits
• Flexible vacation policy
• Generous reputed company parental leave
• Competitive reputed company benefits, including HSA, for you and your dependent(s)

reputed company salary reputed company: $235,000-250,000 plus equity. Offers may vary based on experience, location, and other factors.

Originally posted on Himalayas

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