quantitative software engineer

Qube Research & Technologies

<p><br></p>
<p> <strong>Your future role within QRT:</strong> </p>
<p>As a Quantitative Developer, you'll work in a close-knit global team of Multi-Asset Quant Developers and Researchers. Working directly with Researchers and Portfolio Managers, you'll enhance our research platform to meet the needs of a constantly evolving environment. You will have a large impact on the success of the team by recommending innovative software solutions - solving problems by building new tools and systems.</p>
<p> <strong>Responsibilities</strong> </p>
<ul>
<li>Automate and streamline data preparation and cleaning</li>
<li>Build and support new quantitative trading framework</li>
<li>Industrialize trading strategies developed by quant researchers</li>
<li>Drive "best practice" amongst the researchers and portfolio managers</li>
<li>Continually expand and upgrade the team s software platform to accommodate the changing business needs</li>
</ul>
<p> <strong>Your present skillset:</strong> </p>
<ul>
<li>3-8 years of experience as a software engineer</li>
<li>Python language experience is a must</li>
<li>Ability to multitask, set project priorities and work in a team</li>
<li>Strong communication skills is a must</li>
<li>Ability to work in a fast-paced environment</li>
<li>Very high standards in code quality and good development practices</li>
<li>Experience in finance and/or machine learning would be beneficial</li>
</ul>
<p><br></p>

Quantitative Developer - Python

Meril

<div>
 <p>
  As a
  <strong>
   Quantitative Machine Learning Engineer
  </strong>
  at
  <strong>
   Merli
  </strong>
  , you will help shape the next generation of
  <strong>
   AI-driven trading infrastructure
  </strong>
  . This role sits at the intersection of
  <strong>
   quantitative research, applied ML, and agentic system design
  </strong>
  , with the goal of optimizing high-frequency (HFT), medium-frequency (MFT), and wholesale trading strategies.
 </p>
 <p>
  You&rsquo;ll architect
  <strong>
   adaptive, agent-based ML systems
  </strong>
  that learn from evolving market microstructures, build robust forecasting and optimization models, and work with trading and infrastructure teams to deploy these solutions in
  <strong>
   real-world, low-latency environments
  </strong>
  .
 </p>
 <p>
  <strong>
   Key Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Design &amp; Build Agentic ML Systems:
   </strong>
   Develop autonomous and semi-autonomous agents that perform data acquisition, alpha discovery, backtesting, and execution optimization.
  </li>
  <li>
   <strong>
    End-to-End ML Engineering:
   </strong>
   Architect, train, and deploy ML pipelines for HFT/MFT and wholesale trading, from signal generation to execution integration.
  </li>
  <li>
   <strong>
    Quantitative Research Integration:
   </strong>
   Collaborate with quant researchers to translate theoretical models into production-ready predictive and optimization systems.
  </li>
  <li>
   <strong>
    Market Forecasting:
   </strong>
   Develop deep learning, time series, and reinforcement learning models for price movement prediction and regime detection.
  </li>
  <li>
   <strong>
    Trading Optimization:
   </strong>
   Build reinforcement and meta-learning frameworks that adaptively tune strategy parameters in live environments.
  </li>
  <li>
   <strong>
    Scalable ML Infrastructure:
   </strong>
   Implement real-time inference, model versioning, and continuous learning pipelines for production systems.
  </li>
  <li>
   <strong>
    Performance Evaluation:
   </strong>
   Rigorously validate models with historical and synthetic simulations, ensuring robustness, latency, and financial soundness.
  </li>
  <li>
   <strong>
    Documentation &amp; Collaboration:
   </strong>
   Maintain high standards of reproducibility, version control, and code documentation across research and deployment layers.
  </li>
 </ul>
 <p>
  <strong>
   What You&rsquo;ll Gain
  </strong>
 </p>
 <ul>
  <li>
   Work at the frontier of
   <strong>
    AI, quantitative finance, and agentic automation
   </strong>
   .
  </li>
  <li>
   Collaborate with
   <strong>
    quant researchers, data engineers, and trading teams
   </strong>
   shaping next-gen trading systems.
  </li>
  <li>
   Exposure to
   <strong>
    meta-optimization frameworks
   </strong>
   ,
   <strong>
    reinforcement learning
   </strong>
   , and
   <strong>
    multi-agent orchestration
   </strong>
   .
  </li>
  <li>
   Hands-on experience with
   <strong>
    low-latency ML deployment
   </strong>
   , GPU acceleration, and distributed training in real trading environments.
  </li>
  <li>
   Ownership of models that directly influence
   <strong>
    market-making, forecasting, and strategy execution
   </strong>
   .
  </li>
  <li>
   Continuous learning and experimentation in a
   <strong>
    research-first, innovation-driven
   </strong>
   environment.
  </li>
 </ul>
 <p>
  <strong>
   Qualifications
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s, Master&rsquo;s, or Ph.D. in Computer Science, Applied Mathematics, Financial Engineering, or a related quantitative field.
  </li>
  <li>
   <strong>
    3+ years
   </strong>
   of experience developing and deploying ML models in production (preferably in finance, trading, or large-scale decision systems).
  </li>
  <li>
   Strong proficiency in
   <strong>
    Python
   </strong>
   and ML frameworks:
   <em>
    PyTorch, TensorFlow, scikit-learn, NumPy, Pandas
   </em>
   .
  </li>
  <li>
   Deep understanding of
   <strong>
    supervised, unsupervised, and reinforcement learning
   </strong>
   ,
   <strong>
    time-series modeling
   </strong>
   , and
   <strong>
    probabilistic forecasting
   </strong>
   .
  </li>
  <li>
   Experience building
   <strong>
    scalable data pipelines
   </strong>
   with
   <em>
    Kafka, Flink, or Ray
   </em>
   and deploying models in
   <em>
    Docker/Kubernetes
   </em>
   environments.
  </li>
  <li>
   Knowledge of
   <strong>
    market microstructure
   </strong>
   ,
   <strong>
    portfolio optimization
   </strong>
   , or
   <strong>
    signal-based trading systems
   </strong>
   is highly desirable.
  </li>
  <li>
   Familiarity with
   <strong>
    meta-learning
   </strong>
   ,
   <strong>
    agent-based system design
   </strong>
   , or
   <strong>
    multi-agent coordination
   </strong>
   is a strong plus.
  </li>
  <li>
   Solid analytical, programming, and debugging skills with an emphasis on
   <strong>
    system reliability and latency optimization
   </strong>
   .
  </li>
 </ul>
 <p>
  <strong>
   Preferred Technical Stack
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Languages:
   </strong>
   Python, C++, Rust
  </li>
  <li>
   <strong>
    ML Infrastructure:
   </strong>
   Ray, MLflow, Airflow, Weights &amp; Biases
  </li>
  <li>
   <strong>
    Data Systems:
   </strong>
   Kafka, Redpanda, Redis, QuestDB
  </li>
  <li>
   <strong>
    Model Deployment:
   </strong>
   Triton Inference Server, TorchServe, or custom GPU inference
  </li>
  <li>
   <strong>
    Cloud/Hybrid Setup:
   </strong>
   Kubernetes, ArgoCD, Helm
  </li>
 </ul>
 <p>
 </p>
</div>


Quantitative ML Engineer

Trade W

<div>
 <p>
  <strong>
   Company Description
  </strong>
 </p>
 <p>
  Trade W is a leading multi-asset trading platform with over seven years of industry experience, providing global users with secure, convenient, and efficient access to the financial markets.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Role Description
 </p>
 <p>
  This is a full-time on-site role for a Quantitative
  <span>
   Developer
  </span>
  , located in Dubai.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Responsibilities
 </p>
 <p>
  Market-Making Optimization &amp; Execution
 </p>
 <ul>
  <li>
   Implement quoting logic, inventory targets, dynamic spreads, passive/active switching, and hedge intensity.
  </li>
  <li>
   Link toxicity/mark-out (e.g., VPIN/Kyle &lambda;) to spreads and hedging.
  </li>
  <li>
   Build multi-LP / cross-exchange routing and cost-aware execution
  </li>
 </ul>
 <p>
  Strategy Research &amp; Signal Development
 </p>
 <ul>
  <li>
   Formulate testable hypotheses for MM/stat-arb/funding-basis/order-book/flow-toxicity signals.
  </li>
  <li>
   Engineer features (L1/L2, imbalance, mark-out, volatility, liquidity/impact) and produce evidence-based research notes.
  </li>
  <li>
   Translate findings into parameterized rules and production-ready configs.
  </li>
 </ul>
 <p>
  Backtesting &amp; Performance Evaluation
 </p>
 <ul>
  <li>
   Build trustworthy back tests with cost/slippage/latency/partial-fill modeling and venue-specific constraints.
  </li>
  <li>
   Run walk-forward/rolling validation, capacity &amp; turnover analysis, and P&amp;L attribution (spread, fees, carry/basis, slippage).
  </li>
  <li>
   Perform stress/scenario tests; track Sharpe/IR, max DD, VaR/ES; run ablations to verify signal credibility.
  </li>
 </ul>
 <p>
  Trading Data Analysis &amp; Live Iteration
 </p>
 <ul>
  <li>
   Analyze orders/trades/positions for mark-out, adverse selection, TCA, and market-quality KPIs.
  </li>
  <li>
   Segment users (retail/pro/arb/HFT) to inform MM parameters and routing.
  </li>
  <li>
   Maintain daily dashboards &amp; alerts; monitor backtest&harr;live drift and close gaps quickly.
  </li>
  <li>
   Run parameter/signal A/B experiments; publish concise weekly updates and quarterly roadmaps.
  </li>
  <li>
   Keep runbooks for events/new listings (risk bands, spreads, leverage) and coordinate rollouts with Dev/Risk.
  </li>
 </ul>
 <p>
  Framework &amp; Systems
 </p>
 <ul>
  <li>
   Design an end-to-end framework where research = backtest = simulation = production (unified data, cost/latency models, parameterized configs, experiment tracking, auto-reports).
  </li>
  <li>
   Real-time risk monitoring: inventory/exposure/leverage/hedge deviation/latency/failure-rate with anomaly detection, circuit-breakers, grade-down, and auto-recovery.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Must-have
 </p>
 <ul>
  <li>
   Languages:
   <strong>
    C++
   </strong>
  </li>
  <li>
   Financial modeling &amp; statistics (probability/time-series, microstructure awareness); comfort with perps/futures, funding &amp; basis.
  </li>
  <li>
   Data analysis: Python (pandas/numpy/numba/asyncio/statsmodels/scikit-learn) and strong SQL; careful EDA and reproducible notebooks.
  </li>
  <li>
   Backtesting discipline: cost/impact modeling, leakage controls, validation hygiene.
  </li>
  <li>
   Engineering mindset: clean code, testing, ability to convert research into robust production rules/services.
  </li>
  <li>
   Clear communication: crisp writing, explicit assumptions, defensible conclusions for business/risk stakeholders.
  </li>
  <li>
   2-8 years of experience
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Tech Stack (reference)
 </p>
 <ul>
  <li>
   Languages: C++, Java, Python, SQL
  </li>
  <li>
   Data: PostgreSQL, ClickHouse, kdb+
  </li>
  <li>
   Analysis/Modeling: NumPy, pandas, statsmodels, scikit-learn, PyTorch/TensorFlow, cvxpy, QuantLib, arch
  </li>
  <li>
   Backtesting: vectorbt, backtrader, zipline
  </li>
  <li>
   Visualization: Matplotlib, Seaborn, Plotly, Tableau/PowerBI
  </li>
  <li>
   Workflow: Jupyter, Airflow/Dagste, Git
  </li>
  <li>
   Crypto(Optional): web3.py/ethers/solana-py, Dune/Flipside, Safe/Fireblocks
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Nice-to-have
 </p>
 <ul>
  <li>
   Order-book microstructure, MM/inventory control; toxicity metrics (mark-out/VPIN/Kyle &lambda;).
  </li>
  <li>
   ClickHouse/PostgreSQL, materialized views, high-throughput writes/queries; dashboards (Metabase/Superset/Plotly); experiment/version tracking.
  </li>
  <li>
   Streaming &amp; orchestration: Kafka/Redpanda, Flink or Spark Streaming, Airflow/Dagster; data quality (e.g., Great Expectations).
  </li>
  <li>
   Systems &amp; deployment: Linux, Docker/K8s, Prometheus/Grafana, GitHub Actions, observability/traceability.
  </li>
  <li>
   Production MM or cross-exchange arb track record; FIX/REST/WebSocket integrations (Binance/OKX/Bybit, etc.).
  </li>
  <li>
   Low-latency optimization (zero-copy, lock-free queues, batch I/O, kernel/network tuning).
  </li>
  <li>
   DEX/on-chain analytics (Dune/The Graph; web3.py/ethers/solana-py)
  </li>
 </ul>
</div>


Quantitative Developer (C++)

Universis Capital Partner

C++ Quant Developer Engineer <br> technology - trading developer / hybrid / full time <br><br>
Who are we looking for: <br> <p> <i>C++ Quant Developer Engineer</i> </p> <p>We are looking for a talented quant developer engineer to create secure and functional code. You will provide quality coding solutions for both simple applications and complex information or systems.</p> <p>The candidate must have a passion for technology and code creation. Attention to detail and an analytical mind are essential qualities for a successful application. Design and build superior and innovative software by writing clean and flawless code.</p> <p>The objective is to work directly with our team of traders, engineers, analysts and data scientists to develop our trading algorithmic infrastructure, including; development and creation of trading algorithms, bringing new functionality, integration of third party APIs, integration of new liquidity sources, enhancements to current infrastructure, structuring of financial systems, with a special focus on developing low latency trading systems.</p> <p>The ideal candidate would be passionate about algorithmic and crypto trading, specialized in building low level systems. With knowledge in algorithmic trading based on Data Mining, Big data, Quants, Machine Learning, with predictive and risk management capabilities to implement high frequency and low latency systems, HFT, Market Making, arbitrage systems.</p>
 Responsibilities: <br> <ul> <li>Programming and implementation of commercial algorithms.</li> <li>Collaborate with business analysts and quants to produce algorithm designs and improve agility and execution of strategies.</li> <li>Develop advanced tick-by-tick backtesting simulation systems to enable rapid strategy prototyping and improved research accuracy.</li> <li>Increase performance management by improving risk, quantification.</li> <li>Interact directly with the business or provide support to the commercial, development and operational teams, supervising to implement changes, technological improvements and solve incidents or problems.</li> <li>Transform designs and specifications into high performance code in the appropriate language, creating high quality code with technical documentation.</li> <li>Integrate individual code solutions into higher-level systems. Work to ensure high performance, security and scalability of business applications.</li> <li>Monitor periodically to ensure that it produces the desired results and perform debugging when necessary.</li> <li>Performing upgrades to make code and systems more secure and efficient. Participating in product quality control.</li> <li>Collaborate in the development of our ultra-low latency commercial platform.</li> <li>Integraci n de las API con terceros; intercambios, bancos y corredores entre otros.</li> <li>Design, development and improvement of main libraries.</li> <li>Collaborate with other teams, including; strategy reviews, code and common programming advice.</li> </ul>
 Requirements: <br> <ul> <li>Bachelor's degree in Computer Science, Computer Science or similar.</li> <li>Strong programming skills in C++, Java, XML, Python.</li> <li>Excellent knowledge with relational databases, MySQL, Mongo, Influx technologies.</li> <li>An analytical and problem-solving mindset.</li> <li>Demonstrable ability to discover and correct bugs in code.</li> <li>Ability to work independently, but in a collaborative team environment.</li> <li>Deep curiosity about financial trading and the digital blockchain ecosystem.</li> <li>Entrepreneurial mindset, persistent and disciplined with a high degree of motivation and involvement.</li> <li>High level of English, fluent oral and written communication.</li> </ul>
 Experience: <br> <ul> <li>More than 2 years of proven experience as a C++ programmer.</li> <li>Experience in developing financial algorithms, with predictive analytics and risk control.</li> <li>Experience with AWS, Google Cloud, Linux.</li> <li>Experience in the financial sector: algorithmic developer, High Frequency Trading, Derivatives Trading, Options trading.</li> </ul>
 Other required skills: <br> <ul> <li>Data Mining, Big data, Quants, Machine Learning, HFT, Market Making, Pure and cross, Arbitrage of different modalities.</li></ul>

C++ Quant Developer Engineer

Luxoft

<div><div><h5 class="jobSectionHeader"><b>Project description
</b></h5><p>We're seeking a Senior Software Engineer to design and build robust, scalable systems that support portfolio and risk analytics, order and trade lifecycle processing, and investment strategies. You will work closely with portfolio managers, quantitative analysts, and product teams to develop technology solutions that create tangible business value in the capital markets space.
</p></div><div><h5 class="jobSectionHeader"><b>Responsibilities</b></h5>
<div><div><p>Key Responsibilities (%70 Backend/30% Frontend)
</p></div><div><p>Design and implement end-to-end technology solutions in an Agile environment, collaborating with business and technical partners.
</p></div><div><p>Leverage AWS cloud services to build scalable, cloud-native applications aligned with long-term architecture goals.
</p></div><div><p>Build and maintain CI/CD pipelines, automated tests, and infrastructure-as-code for efficient deployment.
</p></div><div><p>Ensure system performance, reliability, and scalability across mission-critical applications.
</p></div><div><p>Drive engineering excellence through coding best practices, technical mentorship, and peer collaboration.
</p></div></div></div><div><h5 class="jobSectionHeader"><b>Skills</b></h5>
<p>Must have
</p><div><div><p>10+ years of experience with Java in enterprise systems
</p></div><div><p>5+ years of Spring Boot
</p></div><div><p>3+ years of React
</p></div><div><p>5+ years working with relational databases (e.g., PostgreSQL, MySQL)
</p></div><div><p>5+ years developing and deploying systems on AWS
</p></div><div><p>Demonstrated experience in Capital Markets, Portfolio Management, or Risk Analytics
</p></div><div><p>Strong analytical and problem-solving skills
</p></div><div><p>Excellent verbal and written communication skills
</p></div></div><p>Nice to have
</p><div><div><p>Preferred Skills
</p></div><div><p>Familiarity with AWS
</p></div><div><p>Experience with containerization (e.g., Docker, Kubernetes)
</p></div><div><p>Working knowledge of DevOps practices and tools such as Terraform, GitHub Actions, or Jenkins
</p></div><div><p>Exposure to quantitative models, financial data, or multi-asset strategies
</p></div><div><p>Comfortable working in fast-paced, regulated environments with high-performance expectations
</p></div><div><p>What We're Looking For
</p></div><div><p>Independent self-starter who thrives in an entrepreneurial environment
</p></div><div><p>Strong interpersonal skills and ability to communicate with diverse stakeholders, including front-office professionals, PMs, and quants
</p></div><div><p>Highly organized with exceptional attention to detail and the ability to manage multiple priorities
</p></div><div><p>Professional, adaptable, and collaborative team player
</p></div><div><p>Results-oriented mindset with the ability to deliver under tight deadlines
</p></div></div></div><div><h5 class="jobSectionHeader"><b>Other</b></h5>
<div><div><div><p>Languages</p>
<p>English: C2 Proficient
</p></div></div><div><div><p>Seniority</p>
<p>Senior</p></div></div></div></div></div>
<br><div><div><div><p>Mumbai, India
</p></div><p>Req. VR-118730
</p></div><div></div><div><div><p>Java Full Stack
</p></div><div><p>BCM Industry</p>
</div><div><p>30/10/2025
</p></div><div><p>Req. VR-118730</p></div></div></div><p></p>

Full Stack Developer

Trafigura

<div><div>Main Purpose:</div>
Main Purpose<br>
<br>
<ul><li>We are recruiting an experienced Senior Software Engineer to develop core frameworks and services that power advanced data and analytics platform on AWS.</li><li>Spearhead the architectural design and engineering of innovative solutions that drive the evolution of platform&rsquo;s core capabilities.</li><li>Implementation of shared libraries, frameworks, APIs, SDKs, microservices.</li><li>Collaboration with cloud platform engineers, data engineers, data scientists and other software engineers.</li></ul><div></div><div>
Knowledge Skills and Abilities, Key Responsibilities:</div><div>
Knowledge, Skills and Abilities</div><div></div><div>
Technical Skillsets:</div><div></div><ul><li>
Strong data and software engineering experience: Python, Java, PySpark</li><li>
Proficiency in designing, developing and maintaining APIs, client SDKs, microservices.</li><li>
Expertise in enterprise architecture as well as event-driven and serverless architectures.</li><li>
Familiarity with modern data engineering, distributed data processing engines and stream processing patterns</li><li>
Pracitcal knowledge of various testing methodologies and techniques.</li><li>
Experience in containerization and container orchestration engines.</li><li>
Strong experience in cloud technologies, particularly AWS i.e.: Glue/EMR, ECS/EKS, Redshift/Athena</li><li>
Experience with DevOps practices and familiarity with IaC frameworks.</li></ul><div></div><div>
Experience:</div><ul><li>
Minimum 10 years of software engineering experience.</li><li>
Minimum 4 years of data engineering experience.</li><li>
Bachelor&rsquo;s degree or higher in engineering.</li><li>
Prior experience in Investment Bank is preferred.</li></ul><div></div><div>
Competencies:</div><ul><li>
Strong analytical and problem-solving skills.</li><li>
Effective communication and collaborative mindset.</li><li>
Time management and prioritization.</li><li>
Professional management of employee relationships at all levels.</li><li>
Passion for innovation.</li></ul><div></div><div>
Key Relationships and Department Overview:</div><div>
Key Relationships</div><div></div><ul><li>
Internal: Technical and functional stakeholders based in Geneva, UK, Mumbai and other Trafigura locations. Work closely with cloud platform engineers, data engineers and data scientists.</li><li>
External: Strategic outsourcing partners.</li></ul><div></div><div>
Department</div><div><br>
The Data Science and Engineering team researches, develops and provides advanced analytics and data services to the trading business and other commercial operations at Trafigura. It is comprised of Data Scientists, Data Engineers and Quantitative Finance experts. It is a commercially driven, front office aligned team, that works in close partnership with the trading desks, global research and enterprise technology.</div></div>

Senior Software Engineer

Keyrock

<p>Develop and optimise low-latency options trading systems</p><p>Collaborate with quants, traders, and engineers to enhance trading strategies</p><p>Maintain and improve trading infrastructure, ensuring high performance and stability</p><p>Design and implement efficient, scalable, and resilient trading solutions</p><p>Troubleshoot and enhance exchange connectivity and execution speed</p><p>Support functional and component testing for critical trading components</p><p><strong>Technical Skills &amp; Experience</strong></p><p>Strong experience in Rust and/or C++ (C background also considered)</p><p>Prior experience in a trading environment (HFT, Market Making, Prop Trading, or similar)</p><p>Eagerness to become an expert in Rust (if not already)</p><p>Experience with protobuf-based protocols or similar. Exchange connectivity experience (strongly preferred)</p><p>Experience in High-Frequency Options Trading and low-latency systems (nice to have)</p><p><strong>Soft Skills &amp; Competencies</strong></p><p>Ownership &amp; Reliability  Take full responsibility for your work. Write high-quality, maintainable code, meet deadlines, and follow through on commitments. Anticipate and proactively address potential issues before they arise.</p><p>Initiative &amp; Problem-Solving  Approach challenges with a problem-solving entrepreneurial mindset. Make sound, independent judgments and take the initiative to drive solutions rather than waiting for instructions.</p><p>Operational Diligence  Respond strategically to technical and operational challenges, ensuring robust and reliable trading infrastructure while instilling confidence in the team s processes.</p><p>Curiosity &amp; Growth Mindset  Continuously seek to improve your technical skills and knowledge. Stay ahead of industry trends and take the initiative to practice and explore new technologies that excite you. Excellent Communication Skills with a team player mindset, collaborating within a fully remote global team.</p>

C++ Engineer - Trading

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