The next quant firm is a learning system. We’re building an investment firm around an AI researcher: a system that turns an investment idea into a faithful implementation and evidence worth acting on, and learns from every experiment.
We’re a team of researchers and engineers in New York, and we work in person. We’re curious about how things work, quick to put ideas to the test, and willing to question our own assumptions. Build the researcher with us.
The Role
You will work on the core intelligence layer: agents that discover, evaluate, and execute trading ideas. We are especially interested in people who can move between first-principles research and shipping. You should be comfortable reading papers, forming opinions, designing experiments, building systems, and debugging weird empirical results where the answer might be signal, noise, leakage, overfitting, or a bug.
As a member of the founding team, you'll directly impact every level of the business, from product strategy to team culture.
What you'll do
Design, implement, and improve autonomous multi-agent systems that discover, implement, and evaluate investment strategies
Build agentic harnesses that enable agents to use tools, perform research, and critique their own conclusions
Design and conduct experiments to improve system reliability, calibration, and empirical judgment in uncertain environments
Develop robust evaluation frameworks for agent behavior, reasoning, and research outputs
Create contextual corpora/knowledge base to drive and accelerate discovery
Collaborate with quants to learn the domain and teach the agentic system how to navigate the nuances of the problem space
What we're looking for
Bachelor or above in a STEM field. PhD preferred
At least 2 years of work experience, or equivalent depth demonstrated through exceptional research and shipped systems
Experience doing cutting-edge research in AI, machine learning, statistics, mathematics, computer science, physics, finance, or another technical field
Strong empirical judgment. You know the difference between a real result, noise, leakage, a lucky backtest, and a broken experiment
High agency. You can take an ambiguous research direction and turn it into experiments, code, results, and product improvements
Low ego, high standards, fast execution
Compensation
Salary of $150,000/year to $250,000/year
Generous equity in the company
Company-subsidized health insurance including medical, vision, and dental
HSA, FSA, dependent care FSA, and 401(k) plans provided
Regular wellness, commuter and learning subsidies
We are a small founding team with unusually deep experience across machine learning, hedge fund technology, and investment management. We recently raised a seed round from Gradient Ventures and other investors. Join our founding team to build the future of investing!
Skills Required
- Bachelor's degree or higher in a STEM field
- At least 2 years of work experience, or equivalent depth demonstrated through exceptional research and shipped systems
- Experience conducting cutting-edge research in AI, machine learning, statistics, mathematics, computer science, physics, finance, or another technical field
- Strong empirical judgment, including distinguishing real results from noise, leakage, lucky backtests, and broken experiments
- PhD degree
What We Do
Continual Research builds an agentic continual-research AI system that studies financial markets to automatically discover, test, and promote investment signals. Their platform aims to scale research like software so hedge-fund strategies become accessible to individual investors through separately managed accounts. The New York–based startup combines machine learning, systems engineering, and quantitative research to automate idea generation and portfolio execution for broader investor access.
