ML Research Engineer

<p>Get AI-powered advice on this job and more exclusive features.</p><h3>Key Responsibilities:</h3><ul><li>Develop and implement state-of-the-art machine learning models for trading and investment strategies.</li><li>Research and apply techniques such as deep learning, reinforcement learning, and NLP to large-scale financial datasets.</li><li>Optimize and scale ML pipelines for real-time and batch processing.</li><li>Collaborate with quantitative researchers and portfolio managers to translate research into production-grade models.</li><li>Explore alternative data sources and feature engineering techniques to enhance predictive power.</li><li>Contribute to the development of proprietary ML infrastructure and tooling.</li></ul><h3>Requirements:</h3><ul><li>Advanced degree (MSc/PhD) in Machine Learning, Computer Science, Statistics, Applied Mathematics, or a related field.</li><li>Strong experience in designing and implementing ML models, particularly in time-series forecasting, NLP, or deep learning.</li><li>Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or JAX.</li><li>Solid understanding of probability, statistics, and optimization.</li><li>Experience with large-scale data processing frameworks (e.g., Spark, Dask, Ray) is a plus.</li><li>Prior exposure to financial markets, trading, or quantitative research is essential.</li></ul><h3>Seniority level</h3><p>Entry level</p><h3>Employment type</h3><p>Full-time</p><h3>Job function</h3><p>Research</p>

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