Java Quantitative Developer Low Latency

Our client is a leading and well-established player in the Digital Asset and Cryptocurrency Quantitative/Algorithmic trading industry. The business is going from strength to strength, they are currently going through a period of exponential growth and are enjoying record profits The business is actively expanding as there is additional headcount for a number trade platform specialist Java Development with a focus on either/or Quantitative Development or low-latency performance optimization. You will be working on greenfield projects to build out and enhance their low latency trading systems.

THE ROLE:

Working in a fast-paced trading environment as a Quant Developer, where you will collaborate closely with expert traders, quantitative analysts, and engineering specialists to craft and fine-tune trading strategies across both spot and derivative markets. Based directly on the trading floor, you will play a crucial role in enhancing execution logic, automating workflows, and ensuring performance at scale for a high-frequency, multi-exchange setup. You will focus on optimising every component of the trading stack—including multi-threading, network communication, order processing, and execution logic—to achieve ultra-low latency and high throughput. Robust monitoring, alerting, and performance tracking ensure system reliability. The team has deep expertise in trading protocols, messaging systems, network architectures, and concurrent computing to support a complex, high-frequency trading landscape.

KEY RESPONSIBILITIES:

• Build and refine algorithmic trading models for use across various digital asset exchanges
  
  
• Improve and maintain dynamic hedging systems and automated order execution frameworks
  
  
• Achieve top-tier speed and reliability in order processing to maximise execution quality
  
  
• Drive automation of core trading functions to increase scalability and reduce operational risk
  
  
• Partner with quants to develop, back test, and deploy strategic trading logic
  
  
• Create monitoring tools for real-time analysis of trade metrics and strategy efficiency
  
  
• Engineer and optimise ultra-fast connections to trading venues, with a focus on throughput
  
  
• Design architecture capable of handling large volumes in a latency-sensitive environment
  
  
• Implement and manage high-performance messaging frameworks like Aeron and SBE
  
  
• Perform in-depth profiling and tuning to eliminate latency and optimise microsecond-level performance
  
  
• Develop robust order routing and execution components that handle market volatility
  
  
• Apply advanced networking principles to minimise round-trip times and network jitter
  
  
• Continuously assess and remove inefficiencies in JVM performance and memory management
  
  
• Strengthen operational resilience through improved monitoring, alerting, and fault tolerance
  
  SKILL / EXPERIENCE REQUIRED:
  
  
• Expertise in market-making or algorithmic trading, including deep understanding of order book dynamics and pricing techniques
  
  
• Proven track record in Java programming, specifically in building fast, low-latency trading systems
  
  
• Strong familiarity with market data and order execution protocols (e.g. FIX, binary, or custom APIs)
  
  
• Hands-on experience with JVM tuning, garbage collection, and deep performance analysis
  
  
• Knowledge of fast messaging and data serialization technologies for high-speed environments
  
  
• Proficiency in networking concepts, including TCP/UDP, multicast, and low-level optimizations like DPDK or kernel bypass
  
  
• Mastery of concurrent programming, including lock-free algorithms and shared memory architecture
  
  
• Practical experience with Linux performance tuning, including NUMA balancing and use of huge pages
  
  
• Background in high-frequency trading and real-time market operations
  
  
• Ability to design tools for live trade analysis, PnL tracking, and risk alerting
  
  
• Deep understanding of system-level optimization for HFT performance
  
  
• Familiarity with time-series or relational databases for logging and analytics
  
  
• Experience with cloud platforms and containerized infrastructure (AWS, Docker, Kubernetes)
  
  
• Comfortable working in distributed teams across time zones, especially on Linux-based systems
  
  
• Excellent communicator under pressure, able to explain complex systems clearly and concisely
  
  
• A commercially sharp mindset with the ability to balance speed and risk in decision-making