Platinum & Partners is representing a New York-based Systematic Hedge Fund seeking a Quantitative Portfolio Manager to deploy scalable systematic strategies.

The fund trades equities, futures and cross-asset products using data-driven models.

Role Overview

• Own alpha sleeve within systematic framework

• Deploy production-ready strategies

• Optimise portfolio construction

• Collaborate with quant research & engineering

Requirements

• Proven systematic track record

• Strong statistical modelling

• Python / C++ expertise

• Experience within institutional hedge fund environment

Platinum & Partners is a specialist Hedge Fund Recruitment Firm focused on Portfolio Manager hiring, Investment Analysts, Quantitative talent and senior front office professionals across London, Europe, the Middle East and the United States.

The Opportunity

A globally recognised asset manager with a fast-growing systematic investment division is seeking a Portfolio Manager to lead a systematic macro and cross-asset strategy. The firm manages multi-billion assets across discretionary and systematic programmes, and this role represents a rare opportunity to build and run a flagship systematic macro book within an institutional framework with strong infrastructure support.

The Role

As PM, you will design and manage a systematic macro portfolio spanning rates, FX and commodities, working in close partnership with a dedicated quant research team. You will have full ownership of the investment process, strategy roadmap and risk parameters.

• Construct and manage a systematic macro / cross-asset portfolio
• Define and evolve the alpha generation framework for the strategy
• Partner with quant researchers and data scientists on signal and model development
• Engage with senior leadership on capacity, capital allocation and strategy growth
• Represent the strategy in investor-facing and internal forums

Candidate Profile

• Background as a PM, senior researcher or systematic trader in systematic macro, CTA or cross-asset strategies
• Strong grasp of rates, FX and commodities markets from a systematic perspective
• Quantitative foundation — degree in mathematics, physics, engineering or similar
• Experience managing live portfolios or contributing directly to PM-level decisions
• Excellent communication skills for institutional and investor audiences

Compensation

Highly competitive base salary, performance bonus and long-term incentive scheme commensurate with seniority.

One of the most respected multi-strategy quant hedge funds globally is adding a Systematic Portfolio Manager to an elite team. The fund is specifically targeting PMs with a demonstrable, risk-adjusted alpha track record across at least one major asset class equity, rates, FX or commodities within a systematic framework.

What Sets This Opportunity Apart:

This is not a speculative hire. The fund has capital to allocate immediately and will move quickly for a PM who can clearly evidence their edge. You will operate as a fully independent portfolio manager within a multi-strategy structure, supported by world-class infrastructure, data and technology.

The Role:

• Manage an allocated systematic portfolio with full discretion over signal, construction and execution decisions

• Develop and own the research pipeline for your strategy: alpha generation, risk and execution

• Deliver consistent, diversifying alpha with a disciplined, repeatable process

• Collaborate with the central quant research and technology platform

• Manage a small team of researchers and developers within your pod

• Regular performance review and research presentation to the CIO and risk committee

Required Profile:

• 6–15 years of systematic investment experience with direct PM or co-PM responsibility

• Verifiable alpha track record: minimum Sharpe of 1.2+ on a meaningful AUM for 2+ years live

• Expertise in one or more of: equity factors, CTA/trend, macro systematic, stat arb or derivatives

• Ability to discuss strategy performance at signal, factor and portfolio construction level

• Advanced quantitative background — PhD strongly preferred

• Experience at a multi-manager platform (Millennium, Citadel, Balyasny, ExodusPoint, Schonfeld or equivalent) is a significant advantage

Compensation:

• Top-of-market compensation: base, P&L share and long-term incentives

• New-money allocation on joining

The Opportunity

A leading multi-strategy hedge fund with a strong systematic equities franchise is looking to hire an experienced Portfolio Manager to run an alpha-generating book within their systematic equities pod. This is a high-autonomy role with meaningful capital allocation from day one, sitting alongside a team of elite quant researchers and developers.

The Role

You will own a systematic equities portfolio with full P&L accountability, drive signal development in collaboration with the research team, and contribute to the ongoing evolution of the fund's systematic edge. The firm offers significant upside through a competitive carry and bonus structure.

• Run a live systematic equities book with dedicated capital
• Drive alpha research across factor-based and statistical strategies
• Collaborate with quant researchers on new signal generation
• Own the full portfolio construction and risk management process
• Contribute to strategy scaling and capacity management

Candidate Profile

• Proven track record as a PM or senior systematic trader at a hedge fund, prop desk or asset manager
• Deep expertise in equity systematic strategies — stat arb, factor models, market neutral
• Strong quantitative background; comfortable with Python or similar
• Demonstrable alpha generation with risk-adjusted performance record
• London-based or willing to relocate

Compensation

Highly competitive base, discretionary bonus and carry. Structure aligned to long-term PM partnership model.

A top-tier multi-strategy hedge fund is seeking a Systematic Credit Portfolio Manager to build and run a credit-focused systematic book. This is a rare and high-quality pod PM seat for a quant with genuine live track record in systematic credit strategies.

About the Role:

You will manage a systematic credit strategy encompassing corporate bonds, CDS, and credit indices, with full P&L ownership. You will develop and deploy quantitative signals for credit spread prediction, carry, momentum, and relative value — supported by the platform's world-class research and technology infrastructure.

Key Responsibilities:

• Own and manage a systematic credit book with full P&L accountability

• Develop quantitative signals for corporate credit, CDS, and credit index strategies

• Build systematic factor models for credit markets: carry, momentum, quality, value, and relative value

• Oversee portfolio construction, factor exposure management, and risk within credit strategies

• Collaborate with the rates and macro research teams on cross-asset signal integration

• Work with quant developers to productionise research and deploy strategies at scale

• Engage with risk management on drawdown limits, stress scenarios, and credit-specific risk metrics

Required Experience & Qualifications:

• Verified track record running a systematic credit or fixed income strategy with positive risk-adjusted returns

• 6+ years in systematic quantitative research or portfolio management with a credit or fixed income focus

• Deep knowledge of credit markets: corporate bonds, CDS, credit indices (iTraxx, CDX)

• Strong quantitative background — PhD preferred but exceptional track record considered

• Proficiency in Python; C++ experience a plus

• Ability to operate independently within a pod structure

What We Offer:

• Highly attractive payout structure with meaningful capital allocation

• Full platform support: technology, data, risk, and operational infrastructure

• Access to a deep network of experienced credit and quant professionals across the platform

• Significant capital growth potential for strong performers

A well-capitalised multi-strategy hedge fund is seeking a Quantitative Portfolio Manager with a verified, auditable alpha track record in systematic equity strategies. This is a senior seat with immediate capital allocation for the right candidate — the fund is actively competing to secure exceptional PMs before rivals do.

What They Are Looking For:

A PM who has generated genuine, attributable alpha in a systematic equity long/short or statistical arbitrage context. You must be able to demonstrate your edge clearly — through factor exposures, information ratios, Sharpe ratios, and drawdown profiles. Candidates who have run money at a pod within a multi-manager fund, or who have led a systematic equity book at a quant fund, are strongly encouraged to apply.

The Role:

• Run an allocated systematic equity book with full P&L responsibility from day one

• Define the research agenda for your pod: signal research, portfolio construction, execution

• Hire and develop junior researchers and quant developers within your team

• Present strategy performance, risk attribution, and new research to the CIO

• Manage drawdowns proactively and maintain a disciplined risk framework

• Collaborate with the broader quant platform on shared infrastructure and data

Required Profile:

• 5–12 years of systematic investment experience with direct PM responsibility

• Auditable, attributable alpha track record in systematic equity strategies (minimum 2 years live)

• Deep expertise in signal research: price, fundamental, alternative data, or ML-driven factors

• Strong portfolio construction knowledge: optimisation, factor neutralisation, risk budgeting

• PhD or Master's in Mathematics, Statistics, Physics, Computer Science, or Engineering

• Expert Python; C++ or Julia a strong advantage

• Previous experience at a top-tier systematic hedge fund or multi-manager platform preferred

Compensation:

• Highly competitive base salary, with P&L-linked bonus and potential carry

• Immediate capital allocation on day one for the right candidate

A specialist volatility hedge fund is seeking a Systematic Volatility Portfolio Manager to manage a book of options and volatility strategies. This is a PM seat for a quant with a verified live track record in systematic options trading, vol arbitrage, or dispersion — with full P&L ownership and meaningful capital from day one.

About the Role:

You will run a systematic volatility book encompassing equity options, variance swaps, volatility surface trading, and dispersion strategies. The role combines deep derivatives expertise with quantitative rigour — you will own both the research agenda and the live book.

Key Responsibilities:

• Manage a systematic options and volatility book with full P&L accountability

• Develop and continuously improve systematic signals for implied vol, realised vol, and vol surface dynamics

• Construct and manage a portfolio of systematic options strategies: dispersion, variance swaps, skew trades, vol arb

• Oversee Greeks management, delta hedging, and risk within agreed parameters

• Work with quant developers to automate and scale execution and risk management infrastructure

• Conduct ongoing research into vol regime dynamics, term structure anomalies, and cross-asset vol relationships

• Collaborate with the risk team on scenario analysis, tail risk, and drawdown management

Required Experience & Qualifications:

• Demonstrated live track record in systematic volatility, options, or derivatives trading with verifiable P&L

• 5+ years in systematic options trading, volatility research, or derivatives PM at a hedge fund or prop desk

• Deep knowledge of equity options markets, volatility surface dynamics, and derivatives pricing

• Strong quantitative background — PhD in a quantitative field strongly preferred

• Proficiency in Python; C++ or Julia experience a significant advantage

• Ability to operate independently and manage risk in volatile market environments

What We Offer:

• Highly attractive payout structure commensurate with track record

• Meaningful initial capital with growth potential for strong performers

• World-class derivatives infrastructure and data

• Collaborative environment with experienced vol and derivatives professionals

A leading systematic hedge fund is seeking an exceptional Head of Quantitative Research to lead and grow their alpha research function. This is one of the most senior and impactful research roles in systematic finance — the individual will define the research agenda, lead a team of quant researchers, and drive the next generation of alpha strategies.

About the Role:

You will be responsible for setting the research strategy across all systematic equity, macro, and multi-asset strategies. Working directly with the CIO and senior portfolio managers, you will ensure the research function is at the frontier of systematic investment management — technically rigorous, commercially disciplined, and consistently productive.

Key Responsibilities:

• Define and drive the fund's quantitative research agenda across all strategy verticals

• Lead, mentor, and grow a team of quantitative researchers at all levels

• Collaborate with portfolio managers on signal integration, portfolio construction, and strategy evolution

• Maintain the highest standards of research methodology, backtesting rigour, and out-of-sample validation

• Build a culture of intellectual curiosity, collaboration, and performance accountability

• Stay at the frontier of academic research in machine learning, statistics, and quantitative finance

• Work with the CTO and engineering leadership on research infrastructure priorities

• Represent the research function in investment committee and external contexts

Required Experience & Qualifications:

• PhD in Mathematics, Statistics, Physics, Computer Science, or related quantitative field

• 10+ years of quantitative research experience within systematic hedge funds or prop trading firms

• Proven track record developing alpha-generating signals and strategies in live production

• Experience leading research teams of 5+ and setting research strategy at a senior level

• Deep expertise across multiple systematic strategy types (equity, macro, multi-asset)

• Strong programming skills in Python; familiarity with C++ or other high-performance languages

• Exceptional intellectual rigour and an evidence-based approach to research evaluation

What We Offer:

• Highly attractive compensation including significant PnL participation

• Seat at the senior leadership table with real influence over the firm's direction

• World-class research team, data infrastructure, and technology stack

• Opportunity to build and shape a research function at a pivotal growth stage

A derivatives-focused hedge fund is seeking a Volatility Quant Researcher to develop systematic alpha strategies in options and volatility markets. This is a pure research role for someone who combines exceptional mathematical skills with genuine curiosity about volatility dynamics and derivatives pricing. Volatility researchers who can generate systematic, scalable alpha are among the hardest candidates to find and the most aggressively competed for in the quant market.

The Research Focus:

You will research systematic strategies across equity vol, rates vol, and cross-asset implied vol. The fund has significant capacity in volatility markets and is actively building out its quant volatility research capability. Research that passes rigorous validation receives capital allocation quickly.

Key Responsibilities:

• Research systematic alpha strategies in equity and cross-asset volatility markets

• Develop and calibrate volatility surface models (SVI, SABR, local-stochastic vol)

• Build and test systematic strategies: dispersion, variance swaps, skew trading, and vol risk premia

• Analyse implied vs realised vol dynamics and identify systematic mispricings

• Research volatility regime detection and adaptive strategy frameworks

• Collaborate with systematic options traders on strategy refinement and live deployment

• Contribute to the options pricing and risk infrastructure

Required Experience & Qualifications:

• PhD in Mathematics, Physics, Statistics, or Financial Mathematics

• 3–7 years of quantitative research experience in derivatives or volatility markets

• Deep expertise in options pricing theory, vol surface modelling, and derivatives risk

• Expert Python skills; experience with C++ for performance-critical components preferred

• Knowledge of systematic volatility strategies and their return characteristics

• Experience at a derivatives hedge fund, vol trading desk, or quant research group

What We Offer:

• Highly competitive compensation reflecting the scarcity of this skill set

• Access to extensive options data and vol surface analytics infrastructure

• Close collaboration with experienced systematic options traders and portfolio managers

Platinum & Partners is working with a leading systematic hedge fund to identify an exceptional Quantitative Researcher to join their alpha generation team in London. The fund runs systematic strategies across equity and cross-asset markets, with a strong research culture, serious data infrastructure and a direct line from research to live deployment. This is a pure research role. You will own your signals from ideation through to production, no gatekeepers, no committee approval, no running other people's ideas.

THE ROLE

• Research, develop and deploy systematic trading signals across equity and cross-asset markets
• Build and own the full research pipeline: data sourcing, feature engineering, signal construction, backtesting and live implementation
• Integrate alternative data sets into systematic alpha - satellite, NLP, web-scraped, proprietary
• Apply machine learning and statistical techniques to signal generation and portfolio construction
• Collaborate closely with quant developers to bring research into live execution
• Operate with genuine research autonomy within a high-calibre systematic team

WHAT THEY ARE LOOKING FOR

• PhD in Mathematics, Physics, Statistics, Computer Science or a closely related quantitative discipline
• Demonstrable experience generating systematic alpha- live P&L attribution is highly valued, strong backtested research will be considered
• Strong Python skills across the full research stack; familiarity with C++ a plus
• Hands-on experience with machine learning applied to financial data -signal generation, feature engineering, regime detection
• Deep understanding of transaction costs, market microstructure and realistic simulation
• A research mindset that is rigorous, sceptical and obsessed with out-of-sample robustness
• Experience within a systematic hedge fund, prop desk or quantitative asset manager preferred; strong PhDs moving from academia considered

WHY THIS ROLE

• Your alpha trades. Direct pipeline from research to live deployment
• Compensation tied to your contribution - base £180k–£300k, bonus structured around research performance
• Serious data and compute infrastructure- HPC, clean tick data, alternative data budget
• Small, elite research team - no politics, no bureaucracy
• One of the most intellectually demanding and rewarding environments in systematic finance

A systematic fund with a strong execution focus is seeking a Microstructure Quant Researcher to lead research into market impact modelling, alpha decay, and optimal execution. This role sits at the intersection of quantitative research and trading and is one of the most intellectually demanding — and financially rewarding — positions in systematic finance.

The Role:

You will own the research agenda for market microstructure at the fund. Your work will directly improve execution quality and preserve alpha for the fund's systematic strategies. As strategies scale, microstructure research becomes increasingly valuable — and so does your contribution.

Key Responsibilities:

• Research and model market impact, price impact, and alpha decay across equity and derivatives markets

• Develop optimal execution algorithms and VWAP/TWAP enhancement models

• Build transaction cost analysis (TCA) frameworks for strategy evaluation

• Research liquidity provision, adverse selection, and order book dynamics

• Collaborate with quant developers to deploy execution models into the trading stack

• Evaluate broker algorithms and execution venue performance

• Analyse tick data, order book snapshots, and trade data across global markets

Required Experience & Qualifications:

• PhD in Mathematics, Physics, Statistics, Computer Science, or Financial Mathematics

• 3–7 years of microstructure research experience at a hedge fund, bank, or prop trading firm

• Deep knowledge of equity market microstructure, order book dynamics, and execution modelling

• Expert Python skills and experience with high-frequency tick data analysis

• Familiarity with academic market microstructure literature (Almgren-Chriss, Gatheral, etc.)

• Experience with multi-venue execution and dark pool analytics a strong advantage

What We Offer:

• Highly competitive compensation with direct link to execution alpha contribution

• Access to rich, high-resolution tick data across global equity markets

• Collaborative environment with top quant researchers and execution specialists

A systematic hedge fund with a dedicated digital assets division is seeking a Quantitative Researcher to develop alpha-generating strategies across cryptocurrency and digital asset markets. This is a high-conviction hire at a firm committing serious capital and research resources to systematic crypto.

About the Role:

You will research systematic trading strategies across spot and derivatives crypto markets — including on-chain data analysis, market microstructure, momentum, and cross-exchange relative value. The role sits within the broader systematic research team with full access to the firm's data and technology infrastructure.

Key Responsibilities:

• Research and develop systematic alpha signals for cryptocurrency markets (BTC, ETH, altcoins, DeFi)

• Analyse on-chain data including transaction flows, wallet activity, and DeFi protocol metrics as alpha sources

• Build systematic strategies for crypto spot, perpetuals, futures, and options markets

• Research cross-exchange arbitrage, funding rate dynamics, and basis trading opportunities

• Develop market microstructure models specific to crypto market dynamics

• Build rigorous backtesting frameworks accounting for crypto-specific execution costs and liquidity constraints

• Collaborate with portfolio managers on signal integration and portfolio construction

Required Experience & Qualifications:

• 3–7 years of quantitative research experience; background in traditional systematic finance or native crypto quant both considered

• Strong knowledge of cryptocurrency markets, DeFi protocols, and digital asset market structure

• Proficiency in Python; experience with blockchain data tooling (The Graph, Dune Analytics, or similar)

• Rigorous quantitative methodology: statistics, time series analysis, machine learning

• Experience with crypto derivatives (perpetual swaps, options) a strong advantage

• PhD in a quantitative field preferred but strong track record considered

What We Offer:

• Highly competitive compensation with significant performance upside

• Early-mover advantage in institutional systematic crypto — a genuinely frontier research area

• Access to proprietary on-chain data infrastructure and crypto-native datasets

• Collaborative team with deep systematic expertise across both traditional and digital assets

A systematic hedge fund at the frontier of alternative data investing is seeking an NLP and Alternative Data Researcher to build and deploy novel alpha signals from unstructured data. You will combine deep NLP expertise with quantitative finance knowledge to extract investment signals from text, news, earnings transcripts, regulatory filings, and proprietary data sources. Researchers who can connect NLP models to live alpha are among the most sought-after quant professionals globally.

The Opportunity:

The fund has made a strategic commitment to alternative data as a source of differentiated alpha. You will have access to an extensive data library, significant compute resources, and a direct pipeline to the portfolio management team. Research that works gets allocated capital quickly.

Key Responsibilities:

• Develop NLP models for sentiment analysis, topic extraction, and event detection from financial text data

• Build alpha signals from earnings call transcripts, news flow, analyst reports, and social media

• Apply large language models (LLMs) and transformer architectures to financial NLP tasks

• Evaluate signals with rigorous statistical validation: IC, information ratio, and regime analysis

• Research novel alternative data sources and assess their alpha potential

• Collaborate with quant developers to productionise signals and integrate into live strategies

• Present research to portfolio managers and the investment committee

Required Experience & Qualifications:

• PhD in Natural Language Processing, Machine Learning, Computer Science, or a related field

• 2–6 years of NLP or ML research experience — financial context strongly preferred

• Expert Python skills; deep familiarity with Hugging Face, PyTorch, and modern LLM tooling

• Strong understanding of financial markets, corporate events, and investment concepts

• Experience working with large-scale text data pipelines and unstructured data processing

• Track record of generating live, validated alpha signals from text data a significant advantage

What We Offer:

• Highly competitive compensation with direct link to alpha contribution

• Access to an extensive alternative data library and GPU compute cluster

• Fast pathway from research to live capital allocation

A top-tier systematic hedge fund is seeking a Machine Learning Researcher to develop and deploy novel alpha signals using state-of-the-art ML and deep learning techniques. This is a pure research role — you will not be maintaining infrastructure, only generating alpha. You will work directly with portfolio managers and have a direct line from research to capital allocation.

What Makes This Role Stand Out:

The fund has exceptional data infrastructure and is not constrained on compute. You will have access to proprietary and alternative datasets, GPU clusters, and a world-class research platform. Your job is to find edge. Successful researchers here generate some of the most competitive compensation in the industry.

Key Responsibilities:

• Research and develop alpha signals using ML, deep learning, and statistical learning techniques

• Apply models to price, volume, fundamental, sentiment, and alternative data to generate predictive features

• Evaluate signals rigorously: information coefficient, decay, turnover, and regime robustness

• Build ensemble and meta-learning frameworks to combine signals across strategies

• Work closely with portfolio managers to integrate signals into live strategies

• Stay current with the academic literature on financial ML and signal research

• Publish internally and present research at team seminars

Required Experience & Qualifications:

• PhD in Machine Learning, Statistics, Computer Science, Physics, or a closely related quantitative discipline

• 2–6 years of quantitative research experience in a systematic trading or investment context

• Deep expertise in supervised, unsupervised, and reinforcement learning applied to financial data

• Expert Python and PyTorch/TensorFlow skills; experience with large-scale data processing (Spark, Dask)

• Strong statistical rigour: understanding of overfitting, multiple testing, and out-of-sample validation

• Track record of generating novel, live alpha signals a significant advantage

Compensation:

• Highly competitive base salary with substantial performance bonus

• Direct alignment between research output and compensation

A globally recognised systematic hedge fund is seeking a Quantitative Researcher to join their Singapore office, contributing to research across equity and multi-asset systematic strategies focused on APAC and global markets. This is a high-quality research seat at a fund with significant AUM and world-class infrastructure.

About the Role:

You will develop quantitative signals and systematic strategies with a particular focus on Asia-Pacific equity markets, regional macro factors, and cross-asset opportunities. You will work closely with the global research team based in London and New York, contributing original research that feeds directly into live trading strategies.

Key Responsibilities:

• Research and develop alpha signals with an Asia-Pacific market focus: equities, FX, and rates

• Analyse APAC market microstructure, liquidity dynamics, and market-specific data sources

• Build and validate statistical and machine learning models for return prediction in APAC markets

• Develop systematic strategies across equity long/short, pairs trading, and momentum in the region

• Collaborate with the global research team to evaluate cross-regional signal diversification

• Source and evaluate APAC-specific alternative data and news data providers

• Produce research notes and present findings to senior PMs and the global investment committee

Required Experience & Qualifications:

• PhD or strong Master's in Mathematics, Statistics, Physics, Computer Science, or Financial Engineering

• 3–8 years of quantitative research experience at a hedge fund, prop trading firm, or systematic asset manager

• Strong knowledge of Asian equity markets, regional data sources, and APAC market dynamics

• Proficiency in Python; C++ experience beneficial

• Strong grounding in statistical modelling, time series analysis, and machine learning

• Familiarity with systematic trading strategies: momentum, mean reversion, factor investing

What We Offer:

• Highly competitive SGD compensation with strong performance bonus

• Research-led culture with genuine intellectual freedom

• Access to global research team and world-class technology infrastructure

• Singapore-based with regional APAC scope and global collaboration

An elite high-frequency trading firm is seeking a Rust Systems Engineer to design and build the next generation of their core trading infrastructure. This is one of the most technically demanding engineering roles in London for a specialist who is genuinely expert in Rust, cares deeply about latency at the nanosecond level, and wants to work in an environment where engineering excellence is the competitive advantage.

Why Rust:

This firm made a strategic decision to build critical components in Rust for its unique combination of zero-cost abstractions, memory safety without garbage collection and fearless concurrency. You will be working with engineers who have made that same choice for the same reasons, a team that debates memory layout, cache line alignment and branch prediction.

Key Responsibilities:

• Build ultra-low latency trading system components in Rust: market data handlers, order routers, execution engines

• Design lock-free and wait-free data structures for critical hot paths

• Implement kernel bypass networking integrations (DPDK, AF_XDP, Solarflare) from Rust

• Develop shared memory IPC frameworks for inter-process communication with sub-microsecond latency

• Profile and optimise at the hardware level: CPU cache behaviour, NUMA topology, branch prediction

• Collaborate with C++ and Python teams on FFI interfaces and cross-language interoperability

• Build robust testing frameworks: unit, integration and simulation testing for trading components

Required Experience:

• 3+ years of production Rust development; deep familiarity with unsafe Rust, async runtimes and FFI

• Prior experience in HFT, prop trading, or low-latency systems (C++ background strongly preferred alongside Rust)

• Strong Linux internals knowledge: kernel networking, CPU affinity, memory management

• Understanding of exchange protocols and trading microstructure

• Computer Science, Engineering or Physics degree from a leading university

Desirable:

• Contributions to open-source Rust projects in the systems or finance space

• Experience with FPGA interfacing from software

• C++ expertise as a foundation (most strong Rust engineers at this level have it)

A high-performance proprietary trading desk is seeking a C++ Quant Developer who can build and optimise the low-latency execution systems and market data infrastructure that directly determines trading edge. Candidates at this level are competed for aggressively across the prop trading and HFT landscape — compensation is structured to reflect that.

The Environment:

You will join a tight-knit team of exceptional engineers where technical standards are extremely high. Every component you write runs in production daily, processes live market data, and directly affects P&L. This is not an environment for generalist engineers — it is for specialists who care deeply about performance, correctness, and reliability.

Key Responsibilities:

• Build and optimise low-latency C++ components: market data handlers, order routing, and execution engines

• Implement kernel bypass networking (DPDK, Solarflare/OpenOnload) and RDMA where applicable

• Develop lock-free data structures and wait-free algorithms for critical execution paths

• Collaborate with quant researchers to implement strategy logic with minimal latency overhead

• Profile and benchmark system components; own latency reduction from microseconds to nanoseconds

• Build simulation and backtesting infrastructure with tick-level data fidelity

• Maintain production reliability through rigorous testing, monitoring, and incident response

Required Experience & Qualifications:

• 4–10 years of C++ development in an HFT, prop trading, or ultra-low latency environment

• Expert modern C++ (C++17/20): templates, memory management, concurrency, and performance patterns

• Hands-on experience with kernel bypass, DPDK, or network hardware acceleration

• Deep Linux systems knowledge: NUMA, CPU affinity, huge pages, IRQ isolation

• Experience with exchange protocols: ITCH, OUCH, SBE, FIX

• Python for tooling and analysis; FPGA familiarity a significant plus

• Computer Science or Engineering degree from a top university

What We Offer:

• Industry-leading compensation for C++ specialists at this level

• Direct production impact in a live trading environment

• Small, elite engineering team with exceptional technical culture

A well-established systematic fund with a growing multi-asset research team is seeking a Principal Quant Software Engineer to lead the design and delivery of the firm's core research and strategy deployment infrastructure. This is a senior individual contributor and technical leadership role — you will set the engineering standards that the research team works within and directly accelerate the fund's ability to deploy new alpha.

The Opportunity:

Research infrastructure quality is often the difference between a fund that can deploy 10 strategies per year and one that deploys 100. You will own the platform that determines which side of that divide the fund sits on. Your impact on P&L is direct and measurable — which is why the compensation is structured accordingly.

Key Responsibilities:

• Lead the design and implementation of the firm's core backtesting, simulation, and portfolio analytics platform

• Own the data engineering stack: ingestion, normalisation, and storage for market, fundamental, and alternative data

• Define and enforce software engineering standards across the research codebase

• Build deployment pipelines for transitioning research strategies from prototype to live production

• Develop APIs, SDKs, and tooling that allow researchers to iterate quickly without sacrificing rigour

• Work with portfolio managers on risk analytics, attribution, and reporting infrastructure

• Evaluate and adopt new technologies to improve research and execution capabilities

• Mentor quant developers and contribute to hiring standards

Required Experience & Qualifications:

• 7+ years of quantitative software engineering experience at a systematic fund, HFT firm, or top-tier bank

• Expert Python and C++ skills; experience with both research and production codebases

• Proven experience designing and building large-scale backtesting or simulation systems

• Strong data engineering background: time-series databases, Parquet, Kafka, distributed storage

• Deep understanding of quantitative research workflows and systematic strategy development

• Strong software architecture skills and ability to lead technical direction

• Cloud infrastructure experience: AWS or GCP preferred

Compensation:

• Senior compensation package reflecting the principal-level scope and direct research impact

• Discretionary bonus with strong link to team and fund performance

A leading systematic hedge fund is seeking a GPU and High-Performance Computing Engineer to dramatically accelerate the speed and scale of quantitative research. As the fund's signal universe grows and ML models become more central to alpha generation, the ability to run millions of simulations and train large models quickly is a direct competitive advantage — and you will be the person who delivers it.

Why This Role Exists:

The fund's quant researchers are generating more ideas than the current compute infrastructure can evaluate. You will build the GPU-accelerated backtesting, simulation, and model training infrastructure that turns compute constraints into a thing of the past. This is a rare role that few candidates can do well — and compensation reflects that.

Key Responsibilities:

• Design and implement GPU-accelerated backtesting engines and signal computation pipelines

• Optimise numerical computations using CUDA, cuBLAS, cuDNN, and related GPU libraries

• Build distributed computing infrastructure for large-scale cross-sectional and time-series backtests

• Work with ML researchers to accelerate model training and hyperparameter search

• Profile and optimise existing Python/C++ research code for GPU and multi-core CPU execution

• Design memory-efficient data access patterns for large financial datasets

• Evaluate and deploy cloud GPU infrastructure (AWS, GCP) for burst compute workloads

Required Experience & Qualifications:

• 3–7 years of GPU or HPC engineering experience

• Expert CUDA programming skills; experience with OpenCL or ROCm a plus

• Strong C++ and Python skills with experience in scientific computing

• Experience with distributed computing frameworks (Ray, Dask, Spark)

• Understanding of quantitative finance research workflows preferred

• Experience with AWS/GCP GPU instances and containerised deployment

• Degree in Computer Science, Engineering, Physics, or Mathematics from a leading university

What We Offer:

• Highly competitive compensation — among the best in London's technical hiring market

• Direct impact on the fund's research velocity and competitive edge

• State-of-the-art on-premise and cloud GPU infrastructure

• Work alongside some of the best quant researchers in the industry

A leading systematic hedge fund is seeking a Python Quant Developer to build and maintain the research and strategy implementation platform that sits at the heart of their alpha generation process. This is a hybrid developer-researcher role for someone who writes clean, high-performance Python, understands quantitative finance, and takes pride in building robust infrastructure that researchers love to use.

The Opportunity:

You will work directly alongside quant researchers, building the libraries, frameworks and pipelines they depend on to research, backtest and deploy systematic strategies. Your code runs in production. Your architecture decisions shape how research is done.

Key Responsibilities:

• Design and build Python-based research and backtesting frameworks used by the entire quant research team

• Implement alpha signal pipelines: data ingestion, feature engineering, signal generation and evaluation

• Build strategy simulation and portfolio optimisation tooling with rigorous statistical analysis

• Develop data infrastructure integrating market, alternative and proprietary datasets

• Collaborate with researchers on signal implementation, performance attribution and live strategy monitoring

• Maintain production-grade code quality: testing, documentation, version control (Git), CI/CD pipelines

• Profile and optimise Python code for research pipeline throughput (NumPy, pandas, Dask, Numba)

Required Experience:

• 3–8 years of Python development in a quantitative finance environment (hedge fund, prop desk or asset manager)

• Strong Python: NumPy, pandas, SciPy, scikit-learn, and ideally Dask or PySpark for large-scale data

• Solid understanding of systematic trading concepts: signal research, backtesting methodology, transaction costs

• Experience with SQL and time-series databases (kdb+/q, InfluxDB, or similar)

• Git, Linux command line, and production software engineering practices

• Mathematics, Statistics, Computer Science or Physics degree from a top university

Highly Desirable:

• Experience with machine learning in a quant research context (sklearn, PyTorch, TensorFlow)

• Knowledge of options pricing, factor models or portfolio optimisation

• kdb+/q or Rust familiarity a plus

A systematic hedge fund with a multi-billion dollar AUM is seeking a Quantitative Developer to be the bridge between quant researchers and live trading. You will take raw research signals, from price momentum through to ML-derived factors — and build them into production-quality, live-trading strategies. Candidates who can code at research speed without sacrificing production robustness are extremely rare and extremely well paid in this market.

Why This Role Matters:

Researchers generate ideas. Traders need live strategies. You are the person who makes that happen — fast, correctly, and robustly. The best quant developers at hedge funds often earn more than the researchers they support, because flawless implementation is where alpha is preserved or lost.

Key Responsibilities:

• Translate quant research prototypes (Python/R/Matlab) into production trading systems

• Build and maintain signal calculation engines, factor libraries, and portfolio construction pipelines

• Develop robust backtesting and simulation frameworks with rigorous statistical validation

• Implement position sizing, risk controls, and execution logic for live strategies

• Optimise performance-critical research and execution code in Python and C++

• Collaborate daily with quant researchers and portfolio managers

• Build data pipelines for market, fundamental, and alternative data

• Maintain production systems with high reliability and low operational risk

Required Experience & Qualifications:

• 3–8 years of quantitative development experience in a systematic trading or investment context

• Expert Python skills; C++ experience strongly preferred

• Experience building production backtesting or live trading systems

• Solid understanding of quantitative finance: factors, signals, portfolio construction, risk

• Experience with financial data: equities, futures, options, tick data

• Strong software engineering fundamentals: testing, version control, code review

• Master's or PhD in Computer Science, Mathematics, Physics, or Engineering preferred

Compensation:

• Highly competitive base salary with substantial discretionary bonus

• Direct financial alignment with the performance of the strategies you build

One of the most competitive proprietary trading firms in London is urgently seeking an FPGA Engineer to join an elite hardware engineering team. You will design, implement, and optimise FPGA-based components for ultra-low latency market data processing, order entry, and risk controls. This is one of the most sought-after technical roles in systematic trading — candidates with the right background are consistently competed for aggressively.

Why This Role Is Different:

You will not be building generic hardware. Every nanosecond matters. You will work at the absolute frontier of trading technology alongside some of the best FPGA and systems engineers in the industry, on live infrastructure that processes billions of dollars of flow daily.

Key Responsibilities:

• Design and implement FPGA logic (VHDL/Verilog/SystemVerilog) for market data feed handlers, order management, and risk gateways

• Optimise critical path timing to achieve sub-microsecond latency on key execution flows

• Collaborate with quant researchers and traders to translate strategy requirements into FPGA implementations

• Develop and maintain simulation testbenches and verification frameworks

• Evaluate new FPGA hardware platforms and network offload technologies (Alveo, Xilinx UltraScale, Solarflare)

• Work with network and systems engineers on co-location and exchange connectivity

• Contribute to kernel bypass and SmartNIC development as required

Required Experience & Qualifications:

• 3–8 years of FPGA development experience with VHDL, Verilog, or SystemVerilog

• Proven track record of latency optimisation in a trading or telecommunications environment

• Deep understanding of network protocols: UDP multicast, TCP, ITCH, OUCH, FIX

• Experience with Xilinx/AMD Vivado toolchain; Intel Quartus a plus

• Understanding of financial exchange protocols and market data feed architecture

• Strong software skills in C++ for host-side tooling and simulation

• Degree in Electronic Engineering, Computer Engineering, or Computer Science from a leading university

What We Offer:

• Market-leading compensation — one of the highest-paying technical roles in London's trading industry

• Work on live production systems with direct trading impact

• Small, elite engineering team with exceptional colleagues

• State-of-the-art co-location hardware and exchange connectivity