Engineering Lead (ML Research Focus)

We9re seeking a talented Engineering Lead (ML Research Focus) to help us build impactful technology and drive innovation. This role is central to our technical strategy. As our Engineering Lead, you will work with our CEO and our quantitative research leadership to set the direction for our models, infrastructure, and software systems, and oversee the end-to-end development of production AI systems. You will also guide our ML research and translate promising ideas into models that perform in live environments.

Our Head of Quantitative Research owns the overall research and trading roadmap. This role is the machine learning depth underneath it - the person closest to the work, leading day-to-day technical execution, making the calls that turn a roadmap into working models, and raising the level of the engineers around them. We work primarily in person and are looking for candidates based in or willing to relocate to the San Diego area.

Responsibilities and Expectations

This role is expected to be primarily hands-on, with the majority of time spent researching, building, training, and deploying models, while leading day-to-day technical execution across the engineering team.

• ML Research & Model Development
  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.
• Technical Leadership & Mentorship
  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.
• AI-Enabled Engineering Acceleration
  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.
• AI Systems, Data Pipelines & Model Quality
  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.
• Execution Against Trading Objectives
  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.

Who You Are

• Applied ML Engineer: You bring 4-6 years of applied ML / AI experience, including 1-2 years leading technical projects or small teams. You have a strong track record of shipping ML systems to production in environments where model performance directly impacts outcomes.
• Applied Researcher & Problem Solver: You excel at turning ambiguous problems into clear research questions, testable hypotheses, and executable modeling work. You have personally designed models and experiments, not only deployed or integrated existing models, and prioritize measurable performance over novelty for its own sake.
• Strong Technical Foundation: You have hands-on experience with modern ML techniques (e.g., deep learning, sequence models, RL, or time-series modeling). You are fluent in Python and familiar with frameworks such as PyTorch, and have experience working with training pipelines, evaluation systems, and production ML infrastructure.
• A True Lead: This is a hands-on lead role rather than a management role. You expect to spend roughly 80% of your time writing code, conducting research, and building models, and 20% directing technical work and mentoring engineers. You lead by doing the work at a level others want to match, you can carry a project end to end without being managed through it, and you want to stay close to the technology rather than drift into process.

Nice to Have:

• Experience applying ML in quantitative finance or trading
• PhD in ML/AI or similar research experience
• Experience as the most senior ML voice on a small team, working directly with founders or research leadership
• Experience improving ML platforms, data pipelines, or deployment workflows in production systems
• Strong collaboration with Portfolio Managers, traders, or domain experts to translate insights into modeling improvements

What We Offer:

• Competitive Compensation: A competitive base salary and performance-based bonus.
• Meaningful Ownership: The opportunity to build and own a part of something bigger with meaningful equity ownership.
• Comprehensive Benefits: Medical, dental, and vision coverage designed to support you and your family9s well-being.
• Financial and Wellness Support: 401(k), Commuter, FSA, and HSA programs, and additional benefits to support long-term stability.
• Flexible Time Off and Work-Life Balance: Generous vacation, sick leave, and company holidays, with flexibility to recharge when needed.

Additional Information

• This is a primarily in-person role based in San Diego, CA.
• This role requires current authorization to work in the United States; Protogon Research is not able to provide visa sponsorship at this time.