> Markdown version of [/jobs/ext/3787564-machine-learning-engineer-remote](https://www.wearedevelopers.com/jobs/ext/3787564-machine-learning-engineer-remote). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Machine Learning Engineer - Remote

- **Company:** TRENT HOEK OUTDOORS LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $140,000.0 - $175,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Distributed Systems, Fraud Prevention and Detection, Python (Programming Language), Machine Learning, Software Deployment, SQL Databases, Apache Spark, Model Validation, Information Technology
- **Published:** October 16, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/przatlhcof

## About the Role

*At least 4 years of hands-on machine learning experience in a production environment.

*Strong proficiency in Python, SQL, and Spark.

*Deep understanding of machine learning, statistics, and experimental design.

*Experience developing machine learning models from the ground up, rather than relying solely on existing frameworks.

*Professional experience in fraud detection, risk, payments, or trust and safety is required.

*Must be a U.S. citizen or Green Card holder., *Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.

## Description

The Senior Machine Learning Engineer / Applied Scientist will develop and deploy machine learning models for fraud detection and risk decisioning. This role offers ownership across the full machine learning lifecycle, from experimentation and model validation to production deployment.

You'll work with large datasets and distributed computing environments alongside experienced machine learning scientists and engineers. The focus is on developing effective models, improving evaluation methods, and applying advanced statistical and machine learning techniques to real-world business challenges.

Key Responsibilities

*Design, develop, and deploy machine learning models for fraud detection and risk decisioning.

*Manage the full machine learning lifecycle, including experimentation, validation, deployment, and ongoing improvement.

*Analyze and process large-scale datasets using distributed computing environments.

*Develop and refine model evaluation frameworks, performance metrics, and validation methods.

*Apply statistical and machine learning techniques to address complex fraud and risk problems.

*Collaborate with cross-functional stakeholders to improve model performance and deliver measurable business outcomes.