Position Summary<br><br>Two Sigma is a leading quantitative investment management and trading firm. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors.<br><br>Our team of engineers, quantitative researchers and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world’s most complex economic problems.<br><br>The Learning Engineering team’s mission is to create cutting-edge tools that advance AI/ML capabilities for our investment management business. Our work spans from large-scale model distributed training, LLM hosting and fine-tuning capabilities, to learning and scoring across a wide array of techniques.<br><br>We are seeking a Quantitative Software Engineering to contribute to our Learning Engineering efforts. Your goal will be to deliver world-class AI/ML capabilities and integrate new and evolving technologies into our internal ecosystem, advancing our investment management business.<br><br><strong>You Will Take On The Following Responsibilities<br><br></strong><ul><li>Become an authority for the systems underpinning our research areas (ML, Finance, and/or quantitative algorithms) and help evolve these components</li><li>Work closely with our research partners to conceptualize and iterate within new areas of research and development. Quantitative Engineers can have a diverse mandate including:</li><ul><li>Model development: prototyping, testing, and implementing models utilized across Two Sigma</li><li>Quantitative systems: designing new architectures and/or developing systems that power research and trading activities at Two Sigma</li><li>Quantitative tooling: developing and scaling the tools, frameworks, and libraries that are used by our teams to conduct research and build models - improving performance optimization and scalability of these capabilities<br></li></ul></ul><strong>You Should Possess The Following Qualifications<br><br></strong><ul><li>BS in Computer Science, Applied Mathematics, or related technical field</li><li>Minimum 1 year of experience required; 3-10 years of experience preferred</li><li>Professional experience building quantitative software across at least one of the following areas: quantitative finance, math/stats/numeric methods, and machine learning/deep learning</li><li>Experience applying technologies and libraries such as NumPy, SciPy, or scikit-learn</li><li>Experience with scientific computing and algorithm development</li><li>Knowledge of scripting languages such as Python</li><li>A background in building large-scale, real-time, and distributed applications is desired</li><li>While we analyze the data-rich domain of finance, financial experience is not a requirement</li></ul>