Quant Trading Developer (Dex/Cex) Toronto, Canada
Mamoru
About the roleWe are a global proprietary trading firm trading across multiple asset classes. We are hiring a quant trading developer for our crypto desk to trade across DEX and CEX venues, with a primary focus on on-chain execution on DEXs (i.E. Hyperliquid).
This role builds nodes, writes execution code, reduces latency and owns end to end from infrastructure to live P&L.
Key responsibilities
Trading:
Develop, automate, and trade strategies on Hyperliquid with the firm’s capital, i.E. arbitrage, liquidations, and funding capture, and own the resulting P&L.
Live risk:
Manage positions, leverage, margin, and funding exposure in real time within risk limits.
Node infrastructure:
Build and run self-hosted DEX (i.E. Hyperliquid) or other nodes and the execution infrastructure used for live trading.
Latency:
Measure and reduce latency, jitter, and throughput bottlenecks across the full tick-to-trade path, including node sync, market-data handling, network connectivity, order signing, and order submission.
On-chain execution code:
Build and maintain market-data handlers, internal order books, and order-routing logic for Hyperliquid and other on-chain venues.
Monitoring and controls:
Build latency analytics (order round-trip, market-data delay, fill quality) and risk controls i.E. kill switches and position limits.
Requirements
Trading track record:
3+ years track of live quant or systematic prop trading with direct P&L responsibility, i.E. running systematic strategies on perpetual futures and managing positions, leverage, and funding in real time.
On-chain node experience:
Has built and run a node on Hyperliquid or other DEX. Able to explain in depth its architecture, bottlenecks, and the latency trade-off.
On-chain coding:
Strong hands-on with RPC, WebSocket feeds, transaction signing, and smart contract interaction. Python required;
Rust, C++, or Go is a strong plus.
Latency:
Proven record of measuring and reducing execution latency in production. Hands-on with latency profiling, network-level latency, and system tuning such as CPU pinning and async event loops.
Deep understanding of perpetuals, fundings, leverage, liquidations, and on-chain order books.
Solid grasp of exchange microstructure, i.E. order types, order-book events, rate limits.
Bachelor’s degree or above in Computer Science, Engineering, Finance, Mathematics, or a related quantitative field.
Strongly preferred
Trading experience across both DEX and CEX venues, including cross-venue arbitrage.
Background in low-latency or HFT trading, including low-latency techniques i.E. lock-free structures and ring buffers.
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This role builds nodes, writes execution code, reduces latency and owns end to end from infrastructure to live P&L.
Key responsibilities
Trading:
Develop, automate, and trade strategies on Hyperliquid with the firm’s capital, i.E. arbitrage, liquidations, and funding capture, and own the resulting P&L.
Live risk:
Manage positions, leverage, margin, and funding exposure in real time within risk limits.
Node infrastructure:
Build and run self-hosted DEX (i.E. Hyperliquid) or other nodes and the execution infrastructure used for live trading.
Latency:
Measure and reduce latency, jitter, and throughput bottlenecks across the full tick-to-trade path, including node sync, market-data handling, network connectivity, order signing, and order submission.
On-chain execution code:
Build and maintain market-data handlers, internal order books, and order-routing logic for Hyperliquid and other on-chain venues.
Monitoring and controls:
Build latency analytics (order round-trip, market-data delay, fill quality) and risk controls i.E. kill switches and position limits.
Requirements
Trading track record:
3+ years track of live quant or systematic prop trading with direct P&L responsibility, i.E. running systematic strategies on perpetual futures and managing positions, leverage, and funding in real time.
On-chain node experience:
Has built and run a node on Hyperliquid or other DEX. Able to explain in depth its architecture, bottlenecks, and the latency trade-off.
On-chain coding:
Strong hands-on with RPC, WebSocket feeds, transaction signing, and smart contract interaction. Python required;
Rust, C++, or Go is a strong plus.
Latency:
Proven record of measuring and reducing execution latency in production. Hands-on with latency profiling, network-level latency, and system tuning such as CPU pinning and async event loops.
Deep understanding of perpetuals, fundings, leverage, liquidations, and on-chain order books.
Solid grasp of exchange microstructure, i.E. order types, order-book events, rate limits.
Bachelor’s degree or above in Computer Science, Engineering, Finance, Mathematics, or a related quantitative field.
Strongly preferred
Trading experience across both DEX and CEX venues, including cross-venue arbitrage.
Background in low-latency or HFT trading, including low-latency techniques i.E. lock-free structures and ring buffers.
#J-18808-Ljbffr
Vacancy posted 2 hours ago
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