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# ML Engineer II

- **Company:** SUNDAE, INC.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Code Review, Software Debugging, Programming Tools, Distributed Computing Environment, Python (Programming Language), Machine Learning, Azure Machine Learning, Pytorch, Apache Spark, Deep Learning, Kubernetes, Information Technology, Production Code, Xgboost, Dask, Machine Learning Operations
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pelavivja0

## About the Role

* 2+ years of experience as a machine learning engineer or a PhD in Computer Science, Data Science, Statistics, or a related field
 * Proficiency in Python with experience writing production-quality code
 * Experience building and evaluating classification models, preferably gradient-boosted decision trees such as LightGBM, XGBoost, or CatBoost
 * Hands-on experience with deep learning frameworks, with a preference for PyTorch
 * Knowledge of distributed data processing or parallel compute frameworks, such as Spark, Ray, or Dask
 * Experience with ML lifecycle tools like Kubeflow, Airflow, MLflow, or similar platforms
 * Familiarity with AI-powered developer tools to accelerate development workflows
 * Strong problem-solving skills with the ability to translate business scenarios into technical solutions
 * Ability to navigate large codebases, perform debugging, and conduct code reviews effectively
 * Excellent communication skills, both verbal and written, to collaborate with technical and non-technical teams
 * Equivalent practical experience or a Bachelor's degree in a relevant field

## Description

We are seeking a talented Machine Learning Engineer to join our Underwriting ML team. In this role, you will be instrumental in developing and enhancing machine learning systems that facilitate real-time transaction decisions. Your primary focus will be on assessing repayment risks and calculating the expected value of each Affirm checkout, ensuring our underwriting models are accurate, reliable, and scalable. You will collaborate closely with experienced ML engineers, data scientists, platform teams, and cross-functional stakeholders to take models from conception to production, maintaining their health through robust measurement and monitoring practices. This position offers a unique opportunity to work on impactful, high-visibility projects that directly influence our core product offerings and customer experience., * Develop, iterate, and optimize underwriting prediction models using diverse approaches for tabular and sequential data

 * Build and scale feature pipelines and training datasets from proprietary and third-party signals in collaboration with data and platform teams
 * Prototype innovative modeling ideas and features, conduct offline experiments, and implement the best approaches into production with appropriate risk controls
 * Integrate models into batch and real-time decision systems, enhancing their reliability, latency, and operational robustness
 * Instrument and monitor model performance and data health, establishing workflows for retraining and backtesting
 * Collaborate across Engineering, Risk Analytics, Product, and ML Platform teams to define requirements, evaluate tradeoffs, and communicate findings effectively
 * Ensure models adhere to compliance and risk management standards while maintaining high performance


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