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Quantitative Developer - Job Opportunity at Metabit Technology LLC

Singapore, Singapore
Full-time
Mid-level
Posted: August 11, 2025
On-site
SGD 120,000 - SGD 180,000 per year, reflecting Singapore's position as a premium financial technology hub and the specialized nature of quantitative development roles in proprietary trading firms

Key Responsibilities

Drive the complete quantitative strategy lifecycle from research conception to production deployment, directly impacting trading performance and revenue generation through systematic strategy implementation
Architect and develop sophisticated research tools on proprietary backtesting platforms, enabling research teams to accelerate strategy discovery and validation processes
Own and optimize live trading infrastructure, ensuring maximum uptime and performance reliability that directly translates to competitive advantage in high-frequency trading environments
Pioneer reinforcement learning and optimization infrastructure development, positioning the firm at the forefront of AI-driven quantitative trading methodologies
Collaborate on mission-critical distributed systems and data platforms that form the backbone of trading operations, with contributions affecting both research velocity and production trading capacity

Requirements

Education

Bachelor, Master degree from world top university, majoring in Computer Science, Software Engineering, Mathematics, Physics, Statistics, or other related STEM fields

Experience

Not specified

Required Skills

Proficient in Linux environments strong programming skills in both C++ and Python comfortable with scientific computing libraries familiar with common data structures and algorithms Solid foundation in mathematics, especially in probability and statistics Strong communication skills and logical reasoning abilities Comfortable working and communicating in Chinese and English
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Sauge AI Market Intelligence

Industry Trends

The quantitative trading industry is experiencing unprecedented growth in Asia-Pacific markets, with Singapore emerging as a primary hub for systematic trading firms seeking to capitalize on regional market inefficiencies and regulatory advantages. The convergence of traditional quantitative methods with machine learning and reinforcement learning techniques is creating a new generation of hybrid trading strategies that require developers who can bridge the gap between academic research and production-grade systems. There is a significant shift towards real-time, low-latency trading infrastructure in the quantitative space, driven by increasing market competition and the need for microsecond-level execution advantages. This trend is particularly pronounced in Asian markets where electronic trading adoption is accelerating rapidly, creating substantial demand for developers who can optimize both research tools and production trading systems. The integration of alternative data sources and advanced statistical modeling techniques is becoming standard practice in quantitative trading, requiring developers to work with increasingly complex data pipelines and distributed computing architectures. This evolution is driving demand for professionals who combine strong mathematical foundations with enterprise-level software engineering capabilities.

Role Significance

Typically operates within a 15-25 person quantitative team structure, working closely with 3-5 researchers and 4-8 engineering professionals in a collaborative, fast-paced trading environment
This is a mid-to-senior level individual contributor role with significant technical ownership and cross-functional collaboration responsibilities, indicating substantial influence on both research outcomes and production trading performance

Key Projects

Development and optimization of proprietary backtesting frameworks that enable rapid strategy prototyping and validation across multiple asset classes and time horizons Implementation of real-time risk management and order execution systems that process thousands of transactions per second while maintaining regulatory compliance Creation of machine learning infrastructure for reinforcement learning applications in trading, including distributed training systems and model deployment pipelines Design of data ingestion and processing systems that handle terabytes of market data daily from multiple global exchanges and alternative data providers

Success Factors

Mathematical rigor combined with practical software engineering excellence is essential for translating theoretical quantitative models into robust, production-ready trading systems that can operate reliably in live market conditions Strong collaboration and communication abilities are critical for working effectively with quantitative researchers who may have deep mathematical expertise but limited software engineering experience, requiring the ability to translate complex requirements into technical solutions Adaptability and continuous learning mindset is vital in the rapidly evolving quantitative trading landscape, where new mathematical techniques, market structures, and technological innovations constantly reshape optimal approaches to strategy development and implementation Performance optimization expertise becomes crucial when dealing with high-frequency trading requirements where microsecond improvements can translate to significant competitive advantages and revenue impact

Market Demand

Very High - Quantitative developers with combined C++/Python expertise and mathematical backgrounds are among the most sought-after professionals in Singapore's financial technology sector

Important Skills

Critical Skills

C++ and Python programming expertise is absolutely essential as these languages form the backbone of quantitative trading systems - C++ for low-latency execution components and Python for research, prototyping, and data analysis workflows that drive strategy development Strong mathematical foundation, particularly in probability and statistics, is fundamental for understanding the theoretical underpinnings of quantitative strategies and making informed technical decisions about implementation approaches that preserve mathematical properties of trading models Linux proficiency and familiarity with scientific computing libraries are crucial for working effectively in the Unix-based environments that dominate quantitative trading infrastructure and for leveraging the computational tools that enable sophisticated mathematical modeling

Beneficial Skills

Experience with distributed systems and parallel computing frameworks becomes increasingly valuable as trading firms scale their operations and require more sophisticated computational architectures for research and production systems Knowledge of financial markets and trading concepts provides important context for technical decisions and enables more effective collaboration with quantitative researchers and traders who rely on the systems being developed Machine learning and artificial intelligence expertise, particularly in reinforcement learning applications, positions developers at the forefront of the industry's evolution toward AI-driven trading methodologies

Unique Aspects

The combination of traditional quantitative development with reinforcement learning and optimization infrastructure development represents a cutting-edge approach to systematic trading that few firms are pursuing at this level of integration
The emphasis on close collaboration between research and development teams, with developers having direct input into research tool design, suggests a more integrated approach to quantitative strategy development than typically found in traditional financial institutions
The focus on both C++ and Python proficiency along with scientific computing expertise indicates a sophisticated technical stack that bridges high-performance computing requirements with modern data science methodologies

Career Growth

Progression to senior technical roles typically occurs within 2-4 years, with advancement to leadership positions possible within 4-6 years for high performers

Potential Next Roles

Lead Quantitative Developer or Principal Engineer roles with expanded technical leadership responsibilities and oversight of larger development initiatives Quantitative Research roles for those interested in strategy development and mathematical modeling, leveraging deep technical implementation knowledge Trading Technology Architecture positions focusing on large-scale system design and infrastructure optimization across trading organizations

Company Overview

Metabit Technology LLC

Metabit Technology LLC appears to be a technology-focused trading firm or financial technology company with significant investment in proprietary trading infrastructure and quantitative research capabilities, operating sophisticated in-house platforms for strategy development and execution

Positioned as a specialized player in the quantitative trading space with emphasis on technological innovation and research-driven approach to systematic trading strategies
Singapore-based operations suggest focus on Asian markets and positioning to take advantage of the region's growing importance in global electronic trading and financial technology innovation
Likely characterized by high-performance, research-oriented environment with emphasis on technical excellence, collaborative problem-solving, and rapid iteration between research insights and production implementation
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