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The Research Engineer will develop scalable research platforms, collaborate with traders and researchers, and optimize ML tools for trading strategies.

As a Quantitative Developer, you will develop systems for research and production, execute backtesting, and optimize strategies while collaborating with teams.

Design and build ML infrastructure, influence data access and model deployment, partner with researchers to optimize ML models for trading, and mentor engineers.

Conduct ML and deep learning research to build, test, and deploy predictive models for trading. Collaborate with traders, researchers, and engineers to engineer features, preprocess data, prototype algorithms, and improve production research tooling to enhance trading performance.

Lead development and deployment of ML models for trading, drive research and prototyping, oversee data and feature engineering, mentor researchers, and build scalable ML research infrastructure.

Lead efforts in recruiting world-class professionals for trading and research roles, nurturing relationships with candidates and managing partnerships with recruitment agencies.

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Design, implement, and deploy ML inference engines on custom FPGA/ASIC hardware. Perform HW/SW co-design with traders and researchers, optimize neural networks for low latency, and build quantization/compression tools to translate ML frameworks to RTL for rapid production deployment.

This position is an opportunity to fill a form for future job matching after the ASPLOS Conference with IMC Trading.