Quant jobs / PDT Partners

Research Engineer

An engineering role at PDT Partners building the compute and ML infrastructure that quantitative researchers use. It sits between research and engineering.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Build scalable infrastructure for alpha, signal and portfolio research
Speed up research workflows with accelerators and high-performance computing
Maintain and extend the internal research stack
Optimise models for real-time inference

What they ask for

Required

Experience building infrastructure to train or fine-tune large ML models
Strong programming and performance profiling
Python scientific stack and deep-learning libraries such as PyTorch or TensorFlow
Experience with hardware accelerators
Curiosity about hard problems

Preferred

Quant finance experience (not required)

Education: Not stated
Experience: Experienced engineer in ML infrastructure
Languages and tools: Python
PyTorch
TensorFlow

How to prepare

Profile and speed up a PyTorch training job on a GPU
Build a small experiment-tracking and data pipeline
Learn distributed training basics
Study how models are served for low-latency inference

What to study

Apply

Read the full posting on PDT Partners’s site before applying: requirements, location and pay can change after we check them.

View the posting on PDT Partners’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with PDT Partners and doesn’t handle applications.