Performance Engineer

Performance Engineer

We’re looking for an exceptional Performance Engineer to join our growing technology organization. Interviewing at PDT is intentionally focused on finding great people who can build long-term, impactful careers with us.

Performance Engineers at PDT are responsible for deeply understanding and optimizing the systems that enable our trading strategies at scale. You will work at the intersection of software, systems, and hardware to analyze performance, drive infrastructure efficiency, and free up critical compute capacity. Your work directly amplifies researcher velocity and scales our core models, creating massive impact through both cost savings and accelerated innovation. You'll thrive at PDT if you love open-ended problems, diving into GPU optimization and system optimization/design, and are excited to take your discoveries all the way to production at scale.

This is a hybrid position and will require the person to work from our New York City office at a minimum of 3 days a week.

Why join us

PDT Partners has a stellar 30+ year track record and a reputation for excellence. Our goal is to be the best quantitative investment manager in the world, measured by the quality of our products, not their size. PDT’s very high employee-retention rate speaks for itself. Our people are intellectually extraordinary, and our community is close-knit, down-to-earth, and diverse.   

Key Responsibilities

• Analyze and understand system performance to enhance researcher throughput and velocity.
• Focus on infrastructure/system-level efficiency, working across Python, PyTorch, OS, networking, storage, and CPU/GPU layers to optimize compute resource utilization
• Read and understand software layers, providing suggestions/PRs that optimize parts of codebases.
• Free up capacity and reduce costs by improving computational efficiency
• Support scaling of core models by ensuring efficient implementation
• Propose and implement systems to improve performance telemetry
• Conduct proof-of-concept (PoC) evaluations and contribute to system design
• Identify and act on optimization opportunities across the stack

Below is a list of skills and experiences we think are relevant. Even if you don’t think you’re a perfect match, we still encourage you to apply because we are committed to developing our people.

• Strong proficiency in Linux and its associated performance engineering toolset.
• Experience with PyTorch, GPUs and CUDA for optimization.
• Deep understanding and appreciation of what happens at the hardware-software interface.
• Versatile engineering mindset: ability to learn quickly, tackle diverse challenges, and adapt.
• Skills in coding, micro-optimization, and understanding multiple programming languages.
• Ability to analyze performance without being solely focused on heads-down optimization.