Engineering Lead (ML Research Focus)

Protogon Research develops autonomous AI systems for deployment in financial markets through proprietary trading. The Engineering Lead will set technical direction with company and quantitative research leadership, lead hands-on machine learning research and production model development, and oversee engineering execution, infrastructure, and mentorship.

Responsibilities:

• Work closely with our CEO and quantitative research leadership to shape the research agenda, then lead its execution: designing, developing, and deploying the production ML models used in live trading environments. Formulate hypotheses, design experiments, and evaluate new modeling approaches. Improve predictive performance, robustness, and adaptability across changing market conditions, with a strong focus on practical implementation and measurable real-world impact
• Lead the day-to-day engineering work across both ML and broader software systems. Make the technical decisions the team runs on, set the standard through your own work, and mentor engineers so the bar rises across the group. Partner with company leadership on hiring, onboarding, and team development as we grow
• Drive the adoption of AI tools and workflows that help the engineering team move faster across research, software development, planning, documentation, and collaboration, while maintaining high standards for technical rigor and execution
• Contribute to and improve core ML infrastructure, including data pipelines, training workflows, evaluation tooling, and inference systems. Much of this is still being built rather than maintained, and you will have real latitude over how it takes shape. Ensure models are reliable, observable, and performant in both training and production environments
• Work with leadership to identify high-impact modeling opportunities and translate them into executable ML work. Operate in an early-stage environment where objectives may be loosely defined, validating approaches through rapid experimentation and integrating models into evolving systems