Gauntlet leads the field in quantitative research and optimization of DeFi economics. We manage market risk, optimize growth, and ensure economic safety for protocols facilitating most spot trading, borrowing, and lending activity across all of DeFi, protecting and optimizing the largest protocols and networks in the industry. We build institutional-grade vaults for decentralized finance, delivering risk-adjusted onchain yields for capital at scale. Designed by the most vigilant, quantitative minds in crypto and informed by years of research.
As of November 2025, Gauntlet manages over $2B in vault TVL, and optimizes risk and incentives covering over $42 billion in customer TVL. We continually publish cutting-edge research that informs our risk models, alerts, and analysis, and is among the most cited institutions — including academic institutions — in terms of peer-reviewed papers addressing DeFi as a subject. We’re a Series B company with around 75 employees, operating remote-first with a home base in New York City.
As a company, we build institutional-grade vaults that deliver risk-adjusted DeFi yields at scale, powered by automated risk models and off-chain intelligence. Gauntlet curates strategies across Morpho, Drift, Symbiotic, Aera and more, with >$2B in vault TVL and a growing suite of Prime, Core and Frontier vaults.
Our mission is to drive adoption and understanding of the financial systems of the future. We operate with a trader’s discipline and a risk manager’s skepticism: size carefully, stress routinely, unwind decisively. The label equals the package equals the contents. No surprises, just predictable, reliable vaults.
About the Emerging Talent Program
The Gauntlet Emerging Talent Program is designed for new graduates who are eager to apply their quantitative and technical skills to the most pressing challenges in decentralized finance. Upon joining the Gauntlet team, you’ll gain:
Hands-on experience solving high-impact problems in DeFi risk, optimization, and protocol design
Mentorship and training from leading researchers and engineers in crypto and quantitative finance
Exposure to real-world systems securing billions of dollars across the industry
A clear growth path into roles in quantitative research, engineering, and data science.
Responsibilities
Transform mathematical models into production code that powers live trading strategies
Build and optimize vault strategies across multiple asset types (stablecoins, ETH/BTC, restaking tokens, real-world assets)
Conduct comprehensive risk assessment using statistical methods to evaluate liquidity risk, token depeg scenarios, insolvency risk, and interest rate exposure
Design and run controlled experiments to measure strategy performance, including profit/loss analysis, maximum drawdowns, and stress testing
Build data pipelines for strategy simulation, real-time monitoring, and automated trade execution
Create monitoring systems with dashboards and alerts to track market changes, protocol updates, and smart contract events
Develop allocation recommendations with appropriate risk guardrails and rebalancing triggers
Write clear research documentation explaining strategy assumptions, trade-offs, and risk management approaches
Collaborate on public research and internal strategy memos
Qualifications
Currently pursuing Bachelor's or Master's degree in Computer Science, Mathematics, Physics, Electrical Engineering, or related quantitative field with expected 2026 graduation date
Strong programming abilities in Python (experience with SQL, TypeScript, or Rust is a plus) with solid foundation in algorithms and data structures
Statistical and mathematical knowledge including probability, statistics, optimization, and time-series analysis
Understanding of financial risk concepts such as Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), portfolio optimization, leverage mechanics, and automated market maker (AMM) mathematics
Strong communication skills and ability to collaborate effectively in code reviews and strategy discussions
Bonus Points
Academic or personal projects involving numerical methods, risk modeling, or quantitative strategy research
Participation in hackathons or contributions to open-source projects
Familiarity with decentralized finance protocols including lending platforms, decentralized exchanges (DEXs), automated market makers (AMMs), and perpetual futures
Understanding of vault management, yield farming strategies, or cross-chain execution
Experience with real-world asset (RWA) tokenization or liquid staking/restaking protocols
Why Join Gauntlet?
Work on live strategies that manage institutional capital with real market impact
Contribute to transparent, publicly visible vault strategies
Learn from experienced engineers and quantitative researchers who deploy models in production
Gain hands-on experience bridging academic theory with practical trading systems
Clear career progression path toward senior engineering or quantitative research roles
Work alongside a team managing high-visibility public vaults
Receive mentorship from professionals with proven track records in quantitative finance and DeFi
Benefits and Perks
Remote first - work from anywhere in the US & CAN!
Regular in-person company retreats and cross-country "office visit" perk
100% paid medical, dental and vision premiums for employees
$1,000 WFH stipend
Monthly reimbursement for home internet, phone, and cellular data
Unlimited vacation
100% paid parental leave of 12 weeks
Fertility benefits
Opportunity for incentive compensation
Please note at this time our hiring is reserved for potential employees who are able to work within the contiguous United States and Canada. Should you need alternative accommodations, please note that in your application.
The national pay range for this role is $120,000 - $150,000 base plus additional On Target Earnings potential by level and equity in the company. Our salary ranges are based on paying competitively for a company of our size and industry, and are one part of many compensation, benefits and other reward opportunities we provide. Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.
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