Quantitative investment and trading firm built on research and AI
Two Sigma is a New York quantitative investment manager whose stack spans C++, Java, Python, Rust and Go alongside PyTorch, JAX, DeepSpeed and RAPIDS, a mix that points to GPU-scale model training next to latency-sensitive trading code. FPGA adoption and projects on low-latency execution and LLM post-training for financial time series show investment on both the speed and AI fronts. Hiring is accelerating and engineering-heavy.
Two Sigma is a privately held quantitative investment management and trading firm headquartered in New York, NY. It applies data science, AI and quantitative research to investing and trading decisions. The firm employs between 1,001 and 5,000 people and hires in the United States, Japan and the United Kingdom. Its infrastructure runs across AWS, GCP and Azure with Docker and Kubernetes, and its research tooling includes NumPy, Pandas, scikit-learn, PyTorch and TensorFlow.
Two Sigma uses C++, Java, Python, Rust and Go, ML tools like PyTorch, JAX, TensorFlow and DeepSpeed, GPU libraries CuPy and RAPIDS, Apache Spark, and Kubernetes across AWS, GCP and Azure. It is adopting FPGA.
Yes. Hiring is accelerating and engineering is the largest focus, with research, data, HR and finance roles also open, mostly at mid and senior levels.
Two Sigma is hiring in the United States, Japan and the United Kingdom, with headquarters in New York, NY.
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Two Sigma's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.