Remote Machine Learning Researcher

Summary

A quantitative investment and research organization is seeking a Machine Learning Researcher / Engineer to join a collaborative, hands-on team. The role focuses on researching and evaluating machine learning techniques, applying mathematical methods to modeling and feature engineering, developing production-quality research code, and contributing to data pipelines and engineering infrastructure.

Responsibilities

• Research, compare, and evaluate machine learning techniques to determine the best solution for each problem
• Apply statistics, linear algebra, optimization, and related mathematical methods to modeling and feature engineering challenges
• Read research papers and transform promising ideas into practical experiments and implementations
• Develop and maintain structured, scalable research code
• Contribute to data pipelines and engineering infrastructure within a hands-on environment
• Utilize AI tools responsibly while maintaining ownership of technical decisions and code quality

Skills

• Strong mathematical background with practical application to machine learning, feature engineering, and optimization
• Hands-on experience with at least one machine learning framework such as PyTorch, JAX, or XGBoost
• Ability to evaluate multiple modeling approaches and select the most appropriate solution for a given problem
• Experience building organized, maintainable research codebases and driving projects through execution
• Strong problem-solving skills and a genuine interest in learning new techniques and methodologies
• Thoughtful use of AI-assisted development tools with awareness of limitations and code quality considerations
• Applicants must be currently authorized to work in the US on a full-time basis now and in the future
• Experience across multiple machine learning disciplines such as reinforcement learning, neural networks, gradient boosting, random forests, genetic algorithms, or ensemble learning
• GPU optimization and performance tuning experience
• Familiarity with Spark and/or Databricks
• Exposure to cloud environments such as AWS
• Interest in financial markets or quantitative investing. Financial industry experience is not required

Qualifications

Must Haves

• Strong mathematical background with practical application to machine learning, feature engineering, and optimization
• Hands-on experience with at least one machine learning framework such as PyTorch, JAX, or XGBoost
• Ability to evaluate multiple modeling approaches and select the most appropriate solution for a given problem
• Experience building organized, maintainable research codebases and driving projects through execution
• Strong problem-solving skills and a genuine interest in learning new techniques and methodologies
• Thoughtful use of AI-assisted development tools with awareness of limitations and code quality considerations
• Applicants must be currently authorized to work in the US on a full-time basis now and in the future

Nice to Haves

• Experience across multiple machine learning disciplines such as reinforcement learning, neural networks, gradient boosting, random forests, genetic algorithms, or ensemble learning
• GPU optimization and performance tuning experience
• Familiarity with Spark and/or Databricks
• Exposure to cloud environments such as AWS
• Interest in financial markets or quantitative investing. Financial industry experience is not required

Benefits

• Fully Remote Opportunity
• Medical Insurance
• Dental Benefits
• Vision Benefits
• Paid Time Off (PTO)
• 401(k)