Our client is an elite proprietary trading firm founded by MIT and Harvard alumni, consistently delivering 40%+ annual returns across equities and futures. Sitting at the intersection of top-tier academia and high-performance trading, it’s one of the most intellectually rigorous environments in the industry.
Nearly half of the firm’s roughly 40 people hold PhDs from the world’s leading institutions, and that academic depth is matched by cutting-edge execution. They’re now growing across engineering and research to build the next generation of their trading platform and strategies. This is a lean, high-density team where the code you write and the models you build run in production, and your decisions show up directly in PnL.
What you’ll do
Software Engineers & Quant Developers
- Build and optimize the computational infrastructure behind core research and portfolio construction
- Work side by side with researchers to turn new ideas into production trading systems
- Design custom software to process large-scale market data in distributed and single-machine environments
- Write high-performance, multi-threaded code using locks and lock-free primitives
Machine Learning Engineers
- Build and scale the pipelines that train, evaluate, and deploy models on large volumes of market data
- Turn research prototypes into fast, reliable models running in live trading
- Optimize training and inference performance, from data loading to GPU and CPU efficiency
- Develop tooling that helps researchers experiment faster and more rigorously
Researchers
- Develop and test predictive signals and models across equities and futures
- Apply statistics, machine learning, and optimization to noisy, real-world market data
- Design rigorous experiments that separate real effects from overfitting
- See your ideas go from hypothesis to live strategy, with clear feedback on what works
Across every role, you’ll own problems end to end with no layers between you and the result.
What you bring
Software Engineers & Quant Developers
- Around 3+ years of software development experience, with strong C++ skills, low-level debugging, and resource optimization
- Experience working in large, complex codebases behind critical systems
Machine Learning Engineers
- Around 3+ years building and deploying ML systems in production
- Strong Python skills and experience with a framework such as PyTorch; C++ is a plus
- A solid grasp of ML fundamentals and how to make models fast and robust in practice
Researchers
- A strong background in a quantitative field such as mathematics, statistics, physics, computer science, or operations research
- Hands-on experience with statistical modeling or machine learning on real data
- Comfort coding in Python or a similar language to test your own ideas
Everyone
- A genuine love of hard technical problems: performance puzzles, clean abstractions, and understanding systems all the way down
- Intense intellectual curiosity, whether that shows up in mathematics, chess, research, or building things for fun
Nice to have
- A PhD in Computer Science, Mathematics, Physics, Statistics, Operations Research, or a related field (more common among researchers, though not required)
- Strong results in competitions such as IMO, IPhO, IOI, Putnam, or competitive programming; many on the team have them, but it’s not a requirement
- An exceptional academic or professional track record, wherever you earned it
- Prior experience in trading, finance, or working with market data
Why this role
- Rare talent density: a team of about 30, founded by MIT and Harvard alumni, where nearly half hold PhDs
- Proven performance: a privately funded firm compounding at 40%+ per year
- Direct impact: a flat structure with no middle management, where great work shows up immediately in results
- Exceptional compensation: base salaries up to $550k, with fully guaranteed bonuses bringing total cash to $1.5M or higher.
Don’t tick every box? Please apply anyway. Outstanding engineers and researchers come from many paths, and we’d rather hear from you than have you rule yourself out.
Interested? Reply and Goliath Partners will be in touch. The team is small, so openings are limited.