Deep Learning Engineer

Deep Learning Engineer

About the Company

Join a fast-growing AI-driven technology company that's modernising prediction and decision systems for complex, real-world industries. The organisation builds powerful AI platforms that help partners, particularly in travel and transportation - automate commercial decisions, optimise revenue and personalise customer experiences through deep learning-based forecasting and analytics.

With an emphasis on bridging legacy infrastructure with cutting-edge data science, the company's solutions provide real-time insights, dynamic pricing, and revenue optimising recommendations across large, intricate datasets. Nearly hundreds of global partners rely on this platform to make confident automated decisions informed by advanced forecasting and deep neural networks.

Here your work won't sit in a research silo, your models will directly influence sophisticated, live operational systems. The environment values intellectual curiosity, scientific rigour, and practical impact, offering opportunities to publish and present on advancements that truly matter.

Role Overview

We're seeking a Deep Learning Engineer with an exceptional research pedigree, proven expertise in neural networks, and substantial industry experience with time series analysis and forecasting. You'll empower product teams to push the frontier of AI-driven decision intelligence by developing models that power real-time forecasting, optimisation, and predictive insights on complex temporal data.

Key Responsibilities

• Design, develop, and deploy advanced deep learning architectures for time series forecasting, decision intelligence, and sequential prediction.
• Translate research innovations into robust, production-quality systems that operate at scale and influence commercial outcomes.
• Collaborate with cross-functional teams, from ML engineers to product leaders to integrate models into forecasting and optimisation pipelines.
• Conduct rigorous benchmarking and experimentation, applying best practices from academic research to real-world data challenges.
• Drive publications and presentations in top venues, representing both theoretical innovation and applied breakthroughs.

What You Bring

Essential:

• Extensive research background in deep learning - demonstrated through publications in top-tier journals and conferences (NeurIPS, ICML, ICLR, JMLR, etc.).
• Strong experience with neural network models applied to time series, dynamic forecasting, and complex sequential tasks.
• Industry experience implementing and refining forecasting systems in production.
• Proficiency in modern ML frameworks such as PyTorch, TensorFlow, or JAX.
• A track record of applying research results to real-world, high-impact problems.

Highly Valued:

• Experience with real-time prediction systems, probabilistic forecasting, and uncertainty quantification.
• Hands-on expertise with cloud infrastructure and ML-oriented deployment workflows.
• Demonstrated ability to collaborate across research, engineering, and product teams.

Based in Central London

Salary £100,000 - £150,000 +bonus (DEO)

Hybrid working