Machine Learning Engineer

About Our Client:

The organization is a privately held investment research and trading firm that manages its own capital across public markets. It combines discretionary trading expertise with modern artificial intelligence techniques to develop proprietary market insights, research models, and trading strategies.

About the Opportunity:

The Machine Learning Engineer develops AI-driven market models from research concepts through production deployment. Reporting to a senior researcher, this role transforms research ideas into actionable models that run daily and support trading decisions. The position provides an opportunity to contribute to quantitative research while growing through demonstrated technical and research results.

Responsibilities:

• Develop and implement deep learning models using market data, progressing from baseline approaches to production-ready systems.

• Manage the end-to-end machine learning workflow, from raw data collection and preparation through model development and results used for trading decisions.

• Set up and maintain compute environments using local GPU hardware or cloud instances while ensuring stable and cost-effective operation.

• Conduct rigorous model evaluation using leakage-resistant validation and regime-aware testing methodologies.

• Review, reproduce, and critically evaluate recent research in foundation models, time-series analysis, and reinforcement learning.

• Leverage modern AI tools to improve efficiency across coding, data processing, research, and literature review.

Requirements:

• Strong understanding of deep learning fundamentals, including optimization, regularization, sequence models, and attention mechanisms.

• Proficiency in Python and PyTorch, with strong experience using NumPy and pandas for data manipulation and analysis.

• Experience setting up and maintaining small-scale GPU infrastructure, including CUDA, containers, storage, and monitoring.

• Ability to work effectively with time-ordered data and implement appropriate validation techniques to prevent data leakage.

• Ability to reproduce and critically assess academic and technical research papers.

• Demonstrated experience or personal projects involving the independent development and deployment of machine learning models.

• Strong self-direction, problem-solving skills, and ability to work remotely with minimal supervision.

Pay Range and Compensation Package:

• Annual compensation range of $150,000–$200,000, plus bonus.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

TalentHop is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.