Senior Research Engineer – Deep Learning & Time Series
About the Role
My client are a forward-thinking financial organisation looking for a Senior Research Engineer to own the machine learning strategy end to end. This is a rare opportunity to shape the AI direction from the ground up, from research through to production with direct visibility at the leadership level.
What You'll Do
- Define and lead the deep learning research agenda, with a focus on time series modelling in financial markets
- Take models from research hypothesis all the way to production-grade, monitored systems
- Evaluate and apply cutting-edge academic research to real-world financial problems
- Work closely with quant researchers, engineers, and senior stakeholders to embed ML into core decision-making
- Help build and mentor a growing research team
Requirements
- Published research in peer-reviewed venues such as IEEE, ICML, NeurIPS, ICLR, or equivalent
- Deep expertise in time series modelling – financial data experience strongly preferred
- Proven end-to-end ML experience: data pipelines, model development, deployment, and monitoring
- Strong Python and ML engineering skills (PyTorch or JAX)
- PhD in ML, Statistics, Computer Science, or related field (or equivalent research output)
- Ability to communicate complex ideas clearly to both technical and non-technical audiences
Nice to Have
- Experience in asset management, hedge funds, or quantitative trading
- Contributions to open-source ML projects
- Prior tech lead or mentorship experience
What's on Offer
- Full ownership of ML strategy from day one
- Dedicated time and support for continued research and publishing
- Competitive base, performance bonus, and equity
- Hybrid working, flexible culture, and access to institutional-grade data and compute
Senior Research Engineer – Deep Learning & Time Series
About the Role
My client are a forward-thinking financial organisation looking for a Senior Research Engineer to own the machine learning strategy end to end. This is a rare opportunity to shape the AI direction from the ground up, from research through to production with direct visibility at the leadership level.
What You’ll Do
- Define and lead the deep learning research agenda, with a focus on time series modelling in financial markets
- Take models from research hypothesis all the way to production-grade, monitored systems
- Evaluate and apply cutting-edge academic research to real-world financial problems
- Work closely with quant researchers, engineers, and senior stakeholders to embed ML into core decision-making
- Help build and mentor a growing research team
Requirements
- Published research in peer-reviewed venues such as IEEE, ICML, NeurIPS, ICLR, or equivalent
- Deep expertise in time series modelling – financial data experience strongly preferred
- Proven end-to-end ML experience: data pipelines, model development, deployment, and monitoring
- Strong Python and ML engineering skills (PyTorch or JAX)
- PhD in ML, Statistics, Computer Science, or related field (or equivalent research output)
- Ability to communicate complex ideas clearly to both technical and non-technical audiences
Nice to Have
- Experience in asset management, hedge funds, or quantitative trading
- Contributions to open-source ML projects
- Prior tech lead or mentorship experience
What’s on Offer
- Full ownership of ML strategy from day one
- Dedicated time and support for continued research and publishing
- Competitive base, performance bonus, and equity
- Hybrid working, flexible culture, and access to institutional-grade data and compute
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