Senior Machine Learning Engineer

ALT

Senior Machine Learning Engineer optimizing pricing models at Alt. Leading ML lifecycle from training to production for trading card market.

Posted 7/15/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $235,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in optimizing pricing models and underwriting processes while leveraging advanced machine learning techniques. Proficient in managing AWS infrastructure and implementing CI/CD pipelines to ensure efficient model deployment and performance monitoring.

Highest-signal resume keywords

Production-Grade PythonSQL ProficiencyMachine Learning Lifecycle ManagementAWS Infrastructure OwnershipMLflow Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningFeature EngineeringGradient-Boosted EstimatorsEnsemble EstimatorsTime-Decay WeightingK-Fold Cross-ValidationCascading Fallback LogicLLMsAI Development ToolsCI/CD Pipelines

Soft Skills

Pragmatic ApproachCollaboration

Tools & Technologies

MLflowAWSInfrastructure as Code (IaC)

Industry Keywords

Pricing ModelsUnderwriting ModelTrading Card MarketExperiment TrackingModel Registry

Tech Stack

Tools & technologies

AWSCloudPythonScikit-LearnSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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)