Machine Learning Quant Engineer - Investment banking/ XVA
Posted 4 days ago by 1761971611
£1,200 Per day
Inside
Onsite
London
Summary: Senior Quant Machine Learning Engineer position at a leading investment bank in London, focusing on the design and deployment of machine learning models for trading and investment platforms. This front-office role involves collaboration with traders and technologists to drive financial innovation. The position requires extensive experience in quantitative and machine learning engineering within financial institutions. The role is classified as inside IR35 and requires on-site presence four days a week.
Key Responsibilities:
- Design, build, and deploy state-of-the-art ML models for alpha generation, portfolio construction, pricing, and risk management
- Lead ML research initiatives and contribute to long-term modeling strategy across asset classes
- Architect robust data pipelines and scalable model infrastructure for production deployment
- Mentor junior quants and engineers; contribute to knowledge-sharing and model governance processes
- Stay current with cutting-edge ML research (e.g., deep learning, generative models, reinforcement learning) and assess applicability to financial markets
- Collaborate closely with cross-functional teams, including traders, data engineers, and software developers
Key Skills:
- 7+ years of experience in a quant/ML engineering or research role within a financial institution, hedge fund, or tech firm
- Advanced degree (PhD or Master's) in Computer Science, Mathematics, Physics, Engineering, or related discipline
- Strong expertise in modern ML techniques: time-series forecasting, deep learning, ensemble methods, NLP, or RL
- Expert-level programming skills in Python and strong understanding of software engineering best practices
- Experience deploying ML models to production in real-time or high-frequency environments
- Deep understanding of financial markets and quantitative modeling
- Experience in front-office roles or collaboration with trading desks (preferred)
- Familiarity with financial instruments across asset classes (equities, FX, fixed income, derivatives) (preferred)
- Experience with distributed computing frameworks (e.g., Spark, Dask) and cloud-native ML pipelines (preferred)
- Exposure to LLMs, graph learning, or other advanced AI methods (preferred)
- Strong publication record or open-source contributions in ML or quantitative finance (preferred)
Salary (Rate): £1200 per day
City: London
Country: United Kingdom
Working Arrangements: on-site
IR35 Status: inside IR35
Seniority Level: Senior
Industry: IT
Senior Quant Machine Learning Engineer sought by leading investment bank based in the city of London.
**Inside IR35, 4 days a week on site**
The role:
To lead the design and deployment of ML-driven models across our trading and investment platforms. This is a high-impact, front-office role offering direct collaboration with traders, quant researchers, and technologists at the forefront of financial innovation.
Your Role
- Design, build, and deploy state-of-the-art ML models for alpha generation, portfolio construction, pricing, and risk management
- Lead ML research initiatives and contribute to long-term modeling strategy across asset classes
- Architect robust data pipelines and scalable model infrastructure for production deployment
- Mentor junior quants and engineers; contribute to knowledge-sharing and model governance processes
- Stay current with cutting-edge ML research (e.g., deep learning, generative models, reinforcement learning) and assess applicability to financial markets
- Collaborate closely with cross-functional teams, including traders, data engineers, and software developers
What We're Looking For
Required:
- 7+ years of experience in a quant/ML engineering or research role within a financial institution, hedge fund, or tech firm
- Advanced degree (PhD or Master's) in Computer Science, Mathematics, Physics, Engineering, or related discipline
- Strong expertise in modern ML techniques: time-series forecasting, deep learning, ensemble methods, NLP, or RL
- Expert-level programming skills in Python and strong understanding of software engineering best practices
- Experience deploying ML models to production in real-time or high-frequency environments
- Deep understanding of financial markets and quantitative modeling
Preferred:
- Experience in front-office roles or collaboration with trading desks
- Familiarity with financial instruments across asset classes (equities, FX, fixed income, derivatives)
- Experience with distributed computing frameworks (e.g., Spark, Dask) and cloud-native ML pipelines
- Exposure to LLMs, graph learning, or other advanced AI methods
- Strong publication record or open-source contributions in ML or quantitative finance
Please apply within for further details or call on 07393149627
Alex Reeder
Harvey Nash Finance & Banking