- Location
- Remote
- Workplace
- Remote
- Level
- Senior
- Posted
- 2 months ago
About this role
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.
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 underwriting 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 scale, and pushes the boundary of what we can automate.
Why This Role Exists
Alt is at an inflection point - 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 further while bringing down the overhead to run it. This is a high-ownership opportunity to take our pricing and underwriting models from "working" to "excellent" - and to define the ML infrastructure standards that will scale with the 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 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.
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)
Underwriting Performance (Advance disbursement rate vs. Target default rate)
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 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.
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-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.
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: $235,000-250,000 plus equity. Offers may vary based on experience, location, and other factors.
As published by Alt. Applications are handled on their site.
Skills this posting mentions
About Alt
At Alt, we’re on a mission to unlock the value of alternative assets, and looking for talented people who share our vision. Our platform enables users to sell, buy, value, and securely store their collectible cards. And we envision a world where anything is an investable asset. Passionate about trading cards? Search our open roles!
All 16 openings at AltOne click, then it is written
Apply to Alt with a resume written for this role.
Queue Senior Machine Learning Engineer and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Alt’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
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Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
Listed from the job board Alt publishes. Refolk is not the employer and does not handle their hiring. Applications go to Alt directly.