ML Research Engineer
A leading quantitative research firm is seeking a Machine Learning Research Engineer to help design and scale infrastructure that powers advanced ML research. This is a unique opportunity to work at the intersection of machine learning, high-performance computing, and real-world quantitative finance applications.
About the Firm:
With a legacy dating back to the early 1990s, they remain one of the most respected names in quantitative investing. It spun out from a major financial institution. The firm is intentionally selective, prioritizing long-term thinking, deep collaboration, and a culture of intellectual curiosity. It's not trying to be the biggest-just the best at what it does.
What You'll Do:
- Collaborate with researchers to understand evolving ML needs and build scalable infrastructure to support them
- Design and optimize tools for training, fine-tuning, and deploying large ML models
- Maintain and evolve a high-performance internal research stack
- Integrate the latest ML techniques, hardware accelerators, and HPC tools to improve research workflows
- Optimize models for real-time inference in production environments
What They're Looking For:
- Strong programming skills, especially in Python and ML/DL libraries like PyTorch or TensorFlow
- Experience building infrastructure for large-scale ML training and deployment
- Familiarity with hardware accelerators (GPUs, TPUs) and performance optimization
- A curious, problem-solving mindset and a passion for building tools that empower others
- No background in finance required-just a drive to learn and contribute
FAQs
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