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# Machine Learning Research Engineer (Remote)

- **Company:** Motion Recruitment Partners LLC.
- **Location:** Boston, MA, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Amazon Web Services, Artificial Neural Networks, Software Quality, Distributed Systems, Genetic Algorithm, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Reinforcement Learning, Feature Engineering, Pytorch, Random Forest, Apache Spark, Xgboost, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** November 11, 2026
- **Apply:** https://www.dice.com/job-detail/0f622979-cd6b-4ce6-b7bb-da06e81c8412

## About the Role

* Strong background in mathematics, statistics, optimization, or a related quantitative discipline
 * Experience applying machine learning techniques to solve complex business or research problems
 * Proficiency with Python and modern machine learning frameworks such as PyTorch, JAX, XGBoost, or similar technologies
 * Experience designing, testing, and implementing machine learning models
 * Ability to build and maintain organized, scalable research codebases
 * Strong analytical and problem-solving skills
 * Experience evaluating multiple modeling approaches and selecting the best fit for a given problem
 * Ability to take projects from research and experimentation through production-ready implementation

Desired Skills & Experience

 * Experience with reinforcement learning, neural networks, ensemble methods, gradient boosting, random forests, or genetic algorithms
 * GPU optimization and performance tuning experience
 * Familiarity with Spark and/or Databricks
 * Experience working within AWS or distributed computing environments
 * Exposure to large-scale data pipelines and machine learning infrastructure
 * Interest in quantitative finance, investing, or financial markets, Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

## Description

What You Will Be Doing Daily Responsibilities

 * Research and evaluate machine learning techniques to solve challenging quantitative problems
 * Apply advanced mathematical concepts to feature engineering, model development, and optimization efforts
 * Explore new research papers and emerging technologies, translating ideas into practical experiments
 * Develop and maintain scalable machine learning systems and research tooling
 * Build clean, organized, and maintainable code that supports ongoing research efforts
 * Collaborate with engineers and researchers to improve data pipelines and platform capabilities
 * Utilize AI-assisted development tools responsibly while maintaining high standards for code quality and validation
 * Continuously experiment, iterate, and improve model performance based on quantitative results