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# Remote Machine Learning Engineer

- **Company:** ANGENEX, LLC
- **Location:** Jersey City, NJ, United States
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, BASIC (Programming Language), Cloud Computing, Linux, DevOps, Python (Programming Language), Machine Learning, Cloud Services, Tensorflow, SQL Databases, Data Processing, Scripting, Pytorch, Apache Spark, Model Validation, Keras, Pandas, Build Management, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Recurrent Neural Networks, Docker
- **Published:** November 8, 2026
- **Apply:** https://www.careerbuilder.com/job-details/remote-machine-learning-engineer-jersey-city-nj--b7e5e6de-d46d-464c-8d0c-9f8f855e27b2

## About the Role

Machine Learning, Marketing Software, Machine Learning, Sales, Data Science, Statistics, Python Programming/Scripting Language, SQL (Structured Query Language), Ecosystems, Cloud Computing, 1+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.

Proficiency across topics in machine learning and statistics.

Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas)

Broad familiarity with the Python ecosystem and common libraries including Scikit-Learn, XGBoost, PyTorch, Keras, Tensorflow, Pandas, and common ML cloud services.

Familiarity with CNNs, RNN, LSTMs, and the latest research trends.

Experience implementing, deploying, and maintaining production machine learning systems.

Experience monitoring and optimizing model performance.

Experience with Linux, Docker and AWS, and basic development operations.

Advanced degree in computer science, mathematics, statistics or related area of study strongly preferred.

## Description

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and commercial analytics.

Responsibilities

 - Build and deploy the ML pipelines that power the company machine learning platform.

 - Manage MLOps infrastructure to monitor and optimize models.