At a Glance
- Tasks: Design and build innovative trading systems for a revolutionary market platform.
- Company: Join Pod Network, a cutting-edge Web3 startup transforming global markets.
- Benefits: Competitive salary, travel opportunities, and visibility in the crypto community.
- Other info: Be part of a fast-moving team with strong researchers and top market makers.
- Why this job: Make a real impact on how markets operate with your engineering skills.
- Qualifications: Deep understanding of market microstructure and coding experience in Python, Rust, C++, or Go.
The predicted salary is between 60000 - 80000 £ per year.
Pod Network is rebuilding the world's markets from first principles - a global, always-on venue where execution is fast, fair, and provably free of the MEV and manipulation that distort today's exchanges. We're looking for someone who thinks in markets: order books, derivatives, risk, and liquidity. You'll design how our markets actually work and build the primitives that make them tradeable.
About the Role
You'll own the trading and markets layer at the heart of Pod - the order book, perpetuals engine, risk and margin systems, leverage logic, and the financial primitives built on top. This is a markets-first engineering role: your edge is a deep understanding of market microstructure, derivatives, and market making, paired with the ability to turn that knowledge into working code. You'll set the parameters that govern live markets, build and run Pod's internal market maker, and partner with external market makers to bootstrap liquidity across new venues.
What You'll Do
- Improve and maintain Pod's core trading modules: order book, perpetuals engine, risk engine, and leverage/margin systems.
- Configure and tune market parameters - funding, fees, tick/lot sizes, margin tiers, liquidation thresholds - as you launch and operate new markets.
- Design and ship novel on-chain financial primitives: vaults, proprietary/protocol AMMs, prediction markets, and other derivatives.
- Build and operate Pod's internal market maker, and partner with external market makers to deepen liquidity.
- Monitor live markets for health, risk, and anomalies, iterating on parameters and safeguards in response to real flow.
- Work closely with research on incentive design, batch auction mechanics, and settlement models.
Qualifications
Must-have:
- Deep understanding of market microstructure: order books, matching, derivatives (especially perpetuals), margin, liquidation, and funding mechanics.
- Hands-on experience in market making, quant trading, or designing/operating exchange and trading systems.
- Ability to translate markets knowledge into production code (e.g. Python, Rust, C++, or Go) and reason about correctness and edge cases under live trading conditions.
Bonus:
- DeFi / on-chain trading experience: AMMs, perp DEXs, vault strategies, prediction markets.
- Experience with low-latency or high-frequency trading systems.
- Blockchains, consensus, or distributed systems.
What We Offer
- Ownership of one of the most consequential surfaces at Pod, with direct impact on how global markets clear.
- Competitive salary plus meaningful upside.
- A high-impact role in an ambitious, fast-moving team working alongside strong researchers and top market makers.
- Travel opportunities and thought-leadership visibility in the crypto community.
About Pod Network
Pod Network is an early-stage Web3 startup building a revolutionary new layer-1 designed to bring the world's markets on-chain with a Web2-like experience. Our chainless, blockless, leaderless protocol challenges the conventional notion of consensus to deliver fair, MEV-free execution at scale. We're backed by a16z crypto, 1kx, BBF, and Lemniscap, and we're looking for exceptional engineers to help shape the future of decentralized markets.
Quantitative Markets Engineer employer: pod network
At Pod, we pride ourselves on being an exceptional employer, offering a unique opportunity for Remote Backend Engineers to work alongside industry leaders in blockchain technology. Our collaborative environment fosters innovation and personal growth, allowing you to make a significant impact while enjoying the flexibility of remote work. With a commitment to equity and a culture that values your contributions, you'll be part of a pioneering team dedicated to shaping the future of decentralized applications.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Markets Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like pod network!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Quantitative Markets Engineer at pod network.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like pod network.
✨Apply Directly through Our Website
When you find a suitable opening like Quantitative Markets Engineer at pod network, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Quantitative Markets Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at pod network, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at pod network. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at pod network
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at pod network!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.