The Company
This elite quantitative trading firm specializes in deploying sophisticated algorithmic strategies across global equity and futures markets. Known for a high-performance culture that merges deep scientific research with world-class engineering, they manage a massive-scale production environment where precision and reliability are the primary benchmarks for success. The firm prioritizes technical excellence and constant iteration, providing a "zero-legacy" playground for engineers who want to see their work directly impact market liquidity and returns.

The role is open to anyone currently based in, or happy to relocate to Hong Kong, Singapore, Shanghai, Beijing, or New York.
 

The Role
As a Quantitative Product Development Engineer, you will own the reliability and performance of a live trading environment. You will act as the critical link between Quantitative Researchers and the production markets, facilitating the seamless deployment and optimization of complex trading strategies. This is a high-stakes engineering role where you will manage the full product lifecycle—from system architecture and performance tuning across the hardware stack to real-time incident response during active trading hours.
 

Requirements

• Bachelor’s degree or higher in Computer Science or a related technical field.

• Minimum of 2 years of professional experience in high-complexity, mission-critical environments.

• Deep proficiency in the Linux operating system and modern engineering practices (Git, CI/CD, Code Review).

• Strong technical proficiency in C++ with a scripting language, or Python 3 combined with a strongly typed language (e.g., Java, Go, Rust).

• Fluency in both English and Chinese to collaborate effectively within a global, multilingual team.

• A genuine interest in quantitative trading and the technical methods used to enhance service reliability.
   

Why Join?

• Direct Strategy Impact: Work side-by-side with researchers to deploy strategies that generate substantial global returns.

• Technical Sovereignty: Optimize trading systems across the entire stack—computation, storage, networking, and hardware.

• Elite Peer Group: Join a team that values top-tier competitive experience (e.g., ACM/ICPC or NOI/NOIP winners).

• Engineering Excellence: Build and maintain high-performance developer tools and systems where technical quality is never compromised.

The role is open to anyone currently based in, or happy to relocate to Hong Kong, Singapore, Shanghai, Beijing, or New York.

The Company

Headquartered in Asia with key hubs in Singapore, Hong Kong, and New York, this technology-driven trading firm manages close to USD 3 billion in assets. Founded by an elite group of graduates from Stanford, CMU, and Tsinghua, the organization merges advanced AI and machine learning to drive automated investment strategies. They are currently scaling their global data infrastructure to support massive, high-fidelity datasets and complex model training pipelines in a "zero-legacy" technical environment.

The Role

As the Market Data Lead, you will spearhead the design and optimization of a high-throughput platform handling real-time and historical feeds from global exchanges. You will bridge the gap between international data vendors and internal quantitative researchers, ensuring the delivery of low-latency, high-precision data that powers the firm’s competitive edge in the global markets.

• 5+ years of experience in market data engineering within a quantitative trading or hedge fund environment.

• Strong proficiency in C++ with extensive experience in high-performance computing and network data processing.

• Familiarity with market data protocols (e.g., ITCH) and the data structures of major global exchanges.

• In-depth understanding of pcap data processing and the ability to develop efficient parsing tools.

• Proven team leadership skills with a profit-driven mindset and strong business acumen.

• Ability to collaborate closely with research and trading teams to provide optimized data solutions.

• Bachelor’s degree or higher in Computer Science, Financial Engineering, or a related quantitative field.

• Elite Technical Team: Work alongside top-tier engineers and researchers from the world's leading academic institutions.

• Cutting-Edge Stack: Utilize a modern, cloud-native infrastructure optimized for AI-driven quantitative research without technical debt.

• Ownership & Influence: Lead a critical function that directly impacts the firm's global trading performance and expansion.

• Agile Culture: Benefit from a "flat" organizational structure that values technical excellence and rapid execution.

• Competitive Incentives: Enjoy a high-performance bonus structure within a rapidly growing, multi-billion dollar fund.

• Global Footprint: Lead the scaling of data architecture as the firm expands its reach across the US and APAC markets.

The Company
This technology-driven trading firm, with a major presence in Singapore, New York, and Hong Kong, manages close to USD 3 billion in assets. Founded by an elite group of graduates from Stanford, CMU, and Tsinghua, the organization merges advanced mathematics with cutting-edge AI to drive automated investment strategies. They operate a "zero-legacy" technical environment, focusing on continuous optimization of machine learning algorithms to deliver sustainable returns in global equity markets.
 

The Role
As a Quantitative Researcher, you will lead the discovery and modeling of short-horizon statistical signals across massive equity universes. You will leverage high-frequency tick-level and order book data to identify transient inefficiencies and arbitrage opportunities. This is a high-impact role within a dedicated Alpha team, focusing on the end-to-end research lifecycle from signal discovery to production deployment.
 

Requirements

• Open to candidates at both junior and senior levels with experience in alpha research or quantitative signal development., specifically within intraday or short-horizon equity strategies.

• Deep expertise in market microstructure, order flow dynamics, and execution-related features.

• Strong programming skills in Python or C++, with fluency in handling large-scale, high-frequency datasets.

• Proven experience in cross-sectional modeling and statistical arbitrage frameworks across global equities.

• Advanced degree (MS/PhD) in a quantitative field such as Mathematics, Physics, Statistics, or Computer Science.

• Knowledge of execution-aware signal design, including slippage modeling and alpha decay analysis.

• Track record of developing successful signal ideas that have contributed to live PnL.
   

Why Join?

• Elite Research Environment: Work alongside top-tier talent from the world's leading academic and technical institutions.

• Cutting-Edge Technology: Access a modern, cloud-native infrastructure optimized for high-frequency AI research without technical debt.

• Pure Research Focus: Focus on predictive modeling and alpha discovery while collaborating with specialized engineering and trading teams for deployment.

• Global Market Exposure: Develop and deploy strategies across diverse global equity markets, including the US, APAC, and EMEA.

• Flat & Agile Culture: Benefit from a collaborative, meritocratic environment that values rapid execution and technical excellence.

• Significant Growth: Join a rapidly expanding firm that is scaling its footprint and assets under management globally.
   

The Company
This leading global strategic advisory firm is redefining the consulting landscape by integrating high-level human expertise with advanced artificial intelligence. Operating at the intersection of complex data and specialized insights, the organization has launched a dedicated AI department to build an enterprise-scale "Virtual AI Lab".

The firm is currently scaling its technical capacity to process over 100,000 documents per day using state-of-the-art LLMs, creating a "zero-legacy" environment where AI is the core driver of operational efficiency and client value.
 

The Role
As a Senior AI Infrastructure Engineer, you will be the primary architect for the Azure-based platform powering the firm’s AI and data-pipeline workloads. You will lead the design and implementation of modular, IaC-first infrastructure, setting the global standard for Terraform, GitOps, and observability. This is a high-impact position where you will partner directly with AI Systems Architects to build the foundation for next-generation document processing and LLM integration.
 

Requirements

• 8+ years of experience in infrastructure, platform, or distributed-systems engineering.

• Hands-on mastery of Microsoft Azure (AKS, Entra ID, Key Vault, and Azure Monitor).

• Deep expertise in Terraform or OpenTofu with a focus on modular design and GitOps-driven workflows using ArgoCD or Flux.

• Proven experience deploying AI/ML pipelines utilizing frameworks like Haystack, LangChain, or LangGraph.

• Strong proficiency in Python or Go, particularly for optimizing GPU workloads and AI compute.

• Technical understanding of OpenTelemetry for defining SLOs and monitoring AI-cost telemetry.

• Experience ensuring the secure handling of sensitive data through encryption, least-privilege access, and audit logging.
   

Why Join?

• Scale and Sophistication: Build a platform capable of processing massive document volumes using the latest models from OpenAI and Anthropic.

• Greenfield Engineering: Lead an IaC-first build, enforcing policy-as-code and modern observability practices from the ground up.

• High-Visibility Impact: Bridge the gap between experimental AI prototypes and enterprise-scale production systems.

• Elite Technical Squad: Collaborate with a distributed, expert team focused on the intersection of legal, regulatory, and technical data.