Deep Learning Quantitative Researcher

About the role

The firm is seeking a Deep Learning Quantitative Researcher to design and operate core deep‑learning pipelines that drive alpha generation. You will own the full empirical loop from data preparation through production deployment, applying rigorous research discipline in a low‑signal environment.

Key responsibilities

• Design, build and maintain end‑to‑end deep‑learning pipelines for quantitative research, including data preparation, distributed training, evaluation and deployment.
• Lead the research agenda by formulating problems, designing models, training, validating and attributing performance.
• Set standards for model evaluation, prevent data leakage and ensure out‑of‑sample hygiene.
• Provide deep‑learning expertise across teams, advising on architecture, diagnostics and reusable components.

Required profile

• PhD‑level training in Computer Science, Engineering, Physics, Mathematics or Statistics from a top‑20 global university.
• 3–5 years of professional experience applying deep learning to large‑scale problems, preferably in quantitative finance.
• Proven end‑to‑end ownership of a production deep‑learning system or published research line.

Required skills

• Strong Python programming skills.
• Expertise with modern deep‑learning frameworks (e.g., PyTorch, TensorFlow).
• Experience with distributed/multi‑GPU training, mixed‑precision and performance optimization.
• Working knowledge of C++ or CUDA‑level optimization (a plus).
• Familiarity with experiment‑management tools, hyper‑parameter optimization and reproducible research environments.