Quant Developer Jobs in London

Goldman Sachs★3.9 (2.3k)· London

Design, implement, and maintain quantitative models and risk frameworks using C++, Java, or Python for Goldman Sachs' Corporate Treasury division, which manages the firm’s liquidity, funding, balance sheet and capital to maximize net interest income.

Lead a global team owning the Equities Risk technology platform, defining the engineering vision and driving platform modernisation. Work with Java or similar technologies on large-scale, distributed, highly available systems. Provide architectural direction, people management, and technical coaching to senior engineers.

Lead the design and architecture of cloud-native, distributed systems, APIs, and data platforms powering Fasanara Open Quant, a quantitative multi-strategy multi-manager hedge fund. Build core investment, portfolio, risk, and data technology while working directly with portfolio managers, quantitative researchers, and traders.

Java, Kafka, AMQ, Kubernetes, AWS, and MongoDB. You will join a tight-knit team building and supporting systematic trading models for a sports betting hedge fund.

Work with Python, modern AI platforms, LLMs, APIs, distributed systems, MCPs, and tool-use frameworks to build AI-powered applications, assistants, and agentic workflows. You will drive AI adoption across QRT’s High Frequency Trading business, creating tools that improve productivity in research, development, and trading operations.

Citi★3.9 (21k)· London

Work with Core Java (multi-threading, concurrency, memory optimization), CouchbaseDB, Kafka, Apache Storm, and Spring. You will design and optimize a mission-critical, high-throughput FX real-time risk system, collaborating closely with the FX Options Trading desk. You provide technical mentorship to mid-level and junior engineers.

JPMorgan★3.9 (20k)· London

Lead a team building Execute, a real-time front-office trading platform for JPMorgan Chase’s Markets businesses. You will set front-end technical direction, architecting and delivering latency-sensitive, data-intensive UIs using React and TypeScript. This role involves hands-on development, mentoring engineers, and partnering with product and business stakeholders to translate complex trading workflows into high-performance user experiences.

You'll use SQL, Excel, and data visualisation platforms like Lightdash, with exposure to AI/LLMs, to turn customer, trading, and market data into actionable insights. You'll support Marketing, Product, and Commercial teams at Beauty Pie, the world's first luxury beauty and wellness buyers' club.

Invesco★3.9 (499)· London

You will research and develop APIs, high-performance computing algorithms, and portfolio construction tools for the Invesco Vision® platform, using classical statistics, ML, and Generative AI. You will build multi-asset portfolios and employ multi-period simulation tools as part of the Portfolio Construction and Engineering team at the investment firm Invesco.

As a Python 3 engineer, you will design, develop, test and deploy software supporting commodities trading, risk management and market-data processing. You will work directly with traders, analysts and engineers to build systems for trading, logistics, accounting, financing and operations.

Design, develop, and optimize low-latency HFT trading systems using Rust, Tokio, Python, AWS, Linux, and protocols like FIX, REST, and WebSocket. You'll own key components of the capital markets trading stack, collaborating with quants and traders on mission-critical infrastructure.

Work with advanced quantitative research tools and techniques to develop alpha-generating systematic macro strategies. This role is on a lean Systematic Macro Team at a global, multi-strategy hedge fund.

You will work with Rust, React, REST APIs, SQL, Redis, and NGINX to build a cloud-native platform for portfolio management, trading, risk analytics, and AI that replaces legacy institutional investment systems. As an early engineer, you will shape both the product and its architecture alongside the founders and CTO.

You will work with Python, SQL, and financial data pipelines to build APIs and high-performance computing algorithms for Invesco Vision®. The team performs quantitative research, constructs multi-asset portfolios, and develops prediction methods using classical statistics, machine learning, and Generative AI. This role sits within the Portfolio Construction and Engineering team.

Design and optimize high-performance cash equity algorithmic trading systems using Java, Rust, Python, and kdb. The role supports internal and agency electronic execution desks and includes microstructure research, backtesting, and low-latency platform performance analysis.

Build and maintain high-performance, adaptive trading strategies for internal and external clients using Java or C++. The role focuses on US-trading algorithms, back-testing, and low-latency development within Goldman Sachs' Systematic Market Making team.

You will work with Python, machine learning, and predictive modelling to research, develop, and deploy alpha signals and predictive models. You will lead a key part of the European systematic equities alpha research team at a global proprietary trading firm, managing researchers and driving alpha initiatives from idea to production.

You'll work with C#/.NET, Python, VBA and Excel to build and improve tools for a front-office trading desk. You'll sit directly alongside traders to solve real-time issues and adapt applications for Swaps, Bonds, or Equities trades.

You will design and develop high-performance, low-latency Java applications for electronic trading, building trading algorithms, execution platforms, and market connectivity while working with messaging technologies and market data architectures. This front-office engineering team builds mission-critical, low-latency trading systems for a leading financial institution. You will collaborate closely with traders, quants, and product teams.

Luxoft★4.5 (669)· London

You will use kdb+, q, Unix/Linux, and shell scripting to design and maintain tick systems (ticker plant, RDB, HDB) for high-frequency risk data platforms. The team collaborates with Risk functions to build low-latency, scalable solutions. You will also mentor developers and drive performance improvements.

Work with C#, .NET Core, cloud-agnostic (Azure/AWS), and React. Develop front-office trading systems for a commodities and energy trading firm trading Power, Oil, Gas, and energy derivatives. Senior individual contributor role.

You will lead research and deployment of alpha signals and predictive models, using Python and machine-learning frameworks for systematic, intraday trading strategies. You will manage and grow part of the European alpha research team for a global proprietary trading firm. The team size is not specified.

Lead Alpha Researcher role blending hands-on research with leadership; work includes Python, machine learning, predictive modelling, and statistical validation to develop alpha signals for systematic equities. You’ll manage part of the European alpha research team, driving global initiatives for IMC, a global trading firm.

Graduate will use Python, C++, Java, C#, or KDB+/q to build next-generation trading systems, research platforms, and quantitative models for a global investment fund.

Build sophisticated trading and analytics platforms using React, TypeScript, JavaScript, WebSockets, GraphQL, and REST. You’ll create high-performance, real-time data visualizations for traders and quantitative researchers within a leading quantitative investment firm.