Quantitative Researcher (Deep Learning - Quant Strategies Team)
We are looking for research scientists and engineers with proven experience in applying deep learning to achieve state-of-the-art solutions in complex, high-stakes domains. This role combines cutting-edge research with engineering, requiring a passion for building impactful trading models. This role also owns driving continuous improvement in model design, tools, and infrastructure. Your work will span all aspects of the quantitative research process, with potential projects targeting areas such as market analysis, forecasting and trading strategy design. Success in this role requires a dynamic blend of machine learning expertise, statistical rigor and coding ability. Join us and be part of a team transforming scientific research into real-world impact.
Skills You'll Need:
- 5+ years of experience developing DL systems with measurable impact in industry and/or academia. * Proficiency in Python
- Expertise in ML libraries/frameworks such as PyTorch (preferred), TensorFlow, etc.
- Experience with time series forecasting problems especially handling, and preprocessing time series data
- Innovative, self-driven problem solvers with a passion for overcoming complex challenges.
- Strong foundation in mathematics and statistics.
- Desire for a collaborative, team-oriented environment.
- PhD, or Master's Degree in Computer Science, Data Science, Mathematics, Physics (or related subject). * Excellent written and verbal communication skills in English.
Preferred:
- Strong publication(s) at CVPR, ICML, ICLR, NeurIPS, AAAI, or equivalent
- Experience with HPC and distributed large model training
- Quant finance experience/expertise
- LLM experience - fine tuning, prompt engineering, scaling and retrieval augmented generation and evaluation
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