Gauntlet is DeFi’s risk manager. We drive capital efficiency while maintaining economic safety for some of the largest crypto protocols with our simulations. Gauntlet manages risk and incentives for over $9 Billion in assets.

Gauntlet continuously publishes cutting-edge research, making us the most cited peer-reviewed articles in the DeFi industry. We’re a Series B company with ~60 employees operating remote-first with a home base in New York City.

Gauntlet’s mission is to help make blockchain protocols and smart contracts safer and more trustworthy for users. Building decentralized systems creates new challenges for protocol developers, smart contract developers, and asset holders that are not seen in traditional development and investing.

Gauntlet is building a blockchain simulation and testing platform that leverages battle-tested techniques from other industries to emulate interactions in crypto networks. Simulation provides transparency and greatly reduces the cost of experimentation so that teams can rapidly design, launch, and scale new decentralized systems.

In order to grow our impact in the DeFi space we are looking to hire experienced Machine Learning Engineers to help new and established protocols better manage the systems they’ve built. This role will require establishing a strong ability to scope, build, and maintain end-to-end machine learning pipelines in order to dynamically manage and tune protocols under changing market conditions to maximize their growth.

Responsibilities

Own end to end creation of quantitative models, simulations, and machine learning models to dynamically manage risk and optimize DeFi protocols
Develop backend pipelines and automated optimization algorithms for parameter recommendations
Own the whole lifecycle of protocol integrations, including building pipelines, working closely with cross-functional teams to define the data requirements and product offering
Contribute to making our core modeling platform world-class
Build data models and visualizations of public blockchain data and modeling results that provide intuitive analytics to our customers to better understand our recommendations and their protocol

Qualifications

3+ years of professional engineering experience
Proficient at writing code in Python or similar interpreted languages
Experience with scientific computing packages such as Numpy/Scipy, Jupyter, Pandas, etc.
Experience deploying and tuning models in a production setting
Ability to quickly internalize abstract concepts in new domains and strong problem-solving skills
Ability to work independently and within a team, manage multiple projects, and meet deadlines.
Strong communication skills and the ability to work collaboratively in a distributed team environment

Bonus Points

Experience working in the crypto industry is a plus but not required.
Enthusiasm for the space, especially DeFi, is very much desired
Master’s or Ph.D. in quantitative fields like Mathematics, Computer Science, Physics, Economics, or similar fields
Smart contract development experience (e.g. Solidity)
Experience with building models at scale
Published or presented research in the space

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
Laptop, monitor, keyboard and mouse setup provided
$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 $150,000 - $180,000 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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