Machine Learning Research Engineer (Remote)

Motion Recruitment; Boston (MA); On-site; USD 120,000 - 210,000; Full time

Job summary

Motion Recruitment is seeking a Machine Learning Research Engineer to join a highly technical team applying advanced ML techniques to complex problems. You will evaluate multiple approaches, design production-ready models, and build scalable research infrastructure on a data and research platform.

The role emphasizes mathematical rigor, hands-on engineering, and translating research into practical, impactful solutions within a collaborative environment.

Qualifications

• 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 ML 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.

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.

Skills

Quantitative discipline

ML techniques

Python

Model deployment

Research codebase

Analytical skills

Model evaluation

Productionization

Reinforcement learning

Neural networks

Spark/Databricks

AWS/distributed computing

Large-scale data pipelines

Finance interest

Job description

Job Description A quantitative investment firm is seeking a Machine Learning Research Engineer to join a highly technical team focused on applying advanced machine learning techniques to complex, real-world problems. This position is ideal for someone who enjoys combining mathematical rigor with hands-on engineering and wants to see research evolve into practical, impactful solutions.

The team values curiosity, experimentation, and thoughtful decision-making. Rather than forcing problems into a single framework, you'll evaluate multiple approaches, select the most appropriate methodology, and build well-structured solutions that deliver measurable results. You'll have the opportunity to work on challenging machine learning initiatives while contributing to an evolving data and research platform.

Required Skills & Experience

• 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

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

The Offer

• Competitive base salary
• Performance-based bonus opportunity
• Exposure to cutting-edge machine learning research and engineering challenges
• Collaborative and highly technical environment
• Direct impact on research initiatives and technology strategy
• Opportunity to work with modern cloud, distributed computing, and GPU-based technologies

You will receive the following benefits

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

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Posted By: Nick Ramler