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# Machine Learning Engineer (AI/ML)

- **Company:** TRENT HOEK OUTDOORS LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Big Data, Computer Programming, Data Infrastructure, Python (Programming Language), Machine Learning, Software Engineering, Feature Engineering, Model Validation, Data Pipelines
- **Published:** November 13, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pyvyrbnxt4

## About the Role

* At least 5 years of experience in data science, machine learning engineering, or software engineering with applied machine learning responsibilities.
 * Experience building and deploying machine learning or statistical models in production environments.
 * Programming experience in Go or Python.
 * Familiarity with software engineering practices for developing maintainable systems.
 * Experience working with large datasets and building data pipelines for feature generation, model training, or inference.
 * Proficiency in supervised and unsupervised machine learning techniques, including classification, clustering, similarity scoring, and anomaly detection.
 * Ability to evaluate models using sound statistical methods.
 * Understanding of model evaluation tradeoffs involving precision, recall, accuracy, and confidence.
 * Ability to write clear, understandable, testable, and maintainable code.
 * Strong communication skills, including the ability to explain technical concepts, model behavior, and tradeoffs to engineers, researchers, and product managers.

## Description

Censys is seeking a Senior Machine Learning Engineer to develop machine learning models and data-driven systems that classify, label, and enrich large volumes of internet data. This role focuses on transforming raw internet telemetry into high-quality datasets, classifications, and insights that support internal systems and customer-facing products.

You will contribute to the development of Censys's data platform, helping create richer context and identify complex relationships across internet-observed assets and services. The position involves designing and developing applied machine learning workflows while collaborating with engineering, research, security, and product teams to improve data coverage and quality., * Build and improve machine learning models and data-driven systems to classify, cluster, label, and enrich internet-observed assets and services.

 * Design and develop applied machine learning workflows that transform raw internet telemetry into useful context for internal systems and customer-facing products.
 * Collaborate with engineering, research, security, and product teams to identify and develop suitable models and datasets.
 * Build feedback loops to improve model coverage and data quality.
 * Develop feature pipelines and training datasets.
 * Build model evaluation frameworks and confidence-scoring systems.
 * Develop services that operate in cloud or on-premises environments.
 * Apply machine learning, data science, and software engineering expertise across different components of the data platform.