Jobs at Flow Traders

Nine-week, in-person summer internship on Flow Traders' New York trading floor. Interns learn from traders, run trading simulations, develop and test quantitative trading strategies, collaborate with traders and researchers on projects, and engage in structured coursework and intern events.

The Trading Operations Engineer will optimize trading systems, resolve technical issues, manage infrastructure, and collaborate with cross-functional teams to enhance system performance.

Research and develop intraday to few-day quantitative alpha signals and systematic trading strategies for APAC equities and futures. Apply machine learning, high-performance computing, time-series modeling, and market microstructure analysis to create scalable trading models. Collaborate with traders, engineers, and researchers to deploy production-ready strategies and improve quantitative research methodologies, tools, and best practices.

Build and operate trading-critical infrastructure across Linux, on-premise, and multi-cloud environments. Develop reusable Terraform modules, GitHub Actions workflows, Kubernetes platforms, and internal automation in Python or Go. Manage GCP, AWS, Alibaba Cloud, Kafka, Linux provisioning, configuration, patching, and lifecycle operations. Participate in production incident response and a global 24/7 on-call rotation while enabling secure self-service infrastructure for Technology teams.

Defines long-term architecture and engineering standards across enterprise systems, including identity, endpoints, compute, virtualization, operating systems, storage, databases, and SaaS foundations. Leads modernization, cloud migration, automation, platform rationalization, and legacy system retirement. Acts as senior technical authority, mentors engineers, drives architecture decisions, and owns integrations such as SSO, provisioning, APIs, and data flows. The role is a hands-on individual contributor based in London with frequent travel to Amsterdam.

Designs, builds, optimizes, and deploys systematic trading models and algorithms. Analyzes large datasets to identify market patterns and trading signals, collaborates with traders and technologists to move research into production, and monitors model performance. Requires advanced quantitative expertise, strong mathematics and statistics, programming proficiency, and the ability to solve ambiguous problems independently.

Design and optimize low-latency C++ components for market data ingestion, normalization, distribution, order execution, and systematic trading infrastructure. Build tools for quantitative researchers and technical traders, and own components through deployment, monitoring, profiling, and production optimization. Collaborate with engineers, quants, and traders to develop highly scalable systems using modern C++, OS internals, CPU and memory architecture, lock-free concurrency, and low-latency networking.

Provide end-user technical support across Windows systems, office infrastructure, datacenter environments, and trading floors. Manage tickets, troubleshoot hardware and applications, configure workstations and meeting-room technology, provision access, support onboarding and offboarding, monitor systems, maintain asset inventories, respond to high-priority incidents, and document recurring issues. Collaborate with infrastructure, network, Linux, and SRE teams to deliver reliable IT solutions and meet SLA targets.

Lead engineering teams by owning roadmaps, delivery planning, hiring, performance management, career development, team culture, and cross-functional alignment. Partner with technical leads, Trading, and Quant teams to deliver software products, manage dependencies and risks, improve delivery predictability, and align engineering work with company goals.

Lead development and global rollout of a machine learning research framework for training, evaluating, combining, and deploying trading models. Partner with quantitative researchers to test hypotheses, develop systematic trading strategies, and create alpha signals. Build end-to-end machine learning pipelines covering data preprocessing, model training, production deployment, and monitoring while applying modern software engineering, cloud, containerization, and MLOps practices.

Develop quantitative trading strategies for digital asset markets, including pricing, execution, and systematic market-making models. Research and optimize strategies using large-scale market data, machine learning, and high-performance computing, then collaborate with Trading and Technology to deploy them into production. The role requires expertise in systematic trading, electronic markets, market microstructure, and translating quantitative methods into profitable trading outcomes.

Develop and evolve high-performance, distributed trading systems focused on low latency, reliability, scalability, and stability. Translate requirements from traders, quants, and stakeholders into technical solutions, maintain shared libraries, evaluate technologies, and integrate third-party platforms. Own software quality through reviews, testing, deployment, and production adoption. Mentor junior engineers, participate in on-call rotations, and use LLM-augmented development and rapid prototyping.

A two-day Amsterdam quant trading academy for students graduating in 2026 or 2027. Participants will learn about traditional finance, crypto, and ETFs; practice pricing, arbitrage, hedging, and market-making through live simulations; shadow trading desks; and compete in trading games. The event offers insight into Flow Traders and the potential for a full-time Graduate Trader offer.

Manage market and credit risk across APAC trading positions and asset classes, including digital assets. Monitor limits, P&L, exposures, trading strategies, and risk appetite while supporting risk framework development. Build risk models, analytics, reports, and automated processes using Python, SQL, and AI tools. Support treasury, securities lending, and capital management activities while collaborating with Traders, Technology, global Risk teams, and external stakeholders.

Design, build, optimize, and deploy systematic trading models and algorithms. Analyze large datasets to identify market patterns and trading signals, collaborate with traders and technologists to productionize research, and monitor and refine models based on live performance. The role requires advanced quantitative expertise, strong programming skills in Python or C++, and the ability to solve open-ended problems independently.

Develop low-latency trading systems, collaborate with teams to optimize strategies, and ensure software stability and quality. Lead global platform rollout.

The role involves developing trading strategies, collaborating with traders, analyzing data, and designing quantitative models to optimize trading performance.

The Senior Research Engineer will develop a trading model research framework, partnering with researchers to create and optimize trading strategies and models.

Lead development and global rollout of core C++ trading platform components. Implement exchange connectivity (FIX, WebSocket, HTTP), optimize for ultra-low latency (kernel bypass, TLS), build trading algorithms, improve reliability and observability, and collaborate closely with quants and traders to deploy production systems.

Design and implement low-latency C++ trading systems and exchange connectivity. Optimize performance and reliability, develop tools and frameworks for pricing and trading strategies, collaborate with quants and traders, maintain testing suites, investigate production issues, and support deployments and observability.