Machine Learning Researcher / Engineer

You will work on machine learning research, feature engineering, optimization problems, and the continued evolution of data and engineering platforms. The environment encourages exploration of new techniques while maintaining a strong focus on implementation and outcomes. Required Skills & Experience, * 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

This role is ideal for someone with a strong mathematical foundation who enjoys evaluating different machine learning approaches, transforming research into production-quality code, and delivering practical results. The team values intellectual curiosity, thoughtful model selection, experimentation, and strong engineering execution., * 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

Desired Skills & Experience

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

• Fully Remote Opportunity
• Base Salary up to $200,000
• Opportunity to work on challenging machine learning and quantitative research problems
• Collaborative, engineering-focused culture with significant ownership and impact

You will receive the following benefits

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