Research Engineer, Pre-Training

Jump Trading Group is committed to world-class research. We empower exceptional talents in Mathematics Physics and Computer Science to seek scientific boundaries push through them and apply cutting-edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness creativity intellectual honesty and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump research outcomes drive more than superior risk-adjusted returns. We design develop and deploy technologies that change our world fund start-ups across industries and partner with leading global research organizations and universities to solve problems.

Our team is a group of quantitative researchers engineers and ML experts leading foundation model research and trading at Jump. Our mission is to combine emerging techniques and original research to generate signals from financial market data and monetize it globally. We are building the future of ML-powered trading through breakthrough foundation models and were looking for an exceptional Pre-Training Engineer to join our team.

What Youll Do:

As a Pre-Training Research Engineer youll be at the forefront of developing massive-scale foundation models that fundamentally transform how we understand and predict markets where milliseconds matter and no playbook exists. Youll own and drive the entire training stack: building fault-tolerant infrastructure that scales across thousands of GPUs and TPUs with near-linear performance engineering data pipelines that stream terabytes per second as our models train on petabytes of data from every corner of the global markets and designing custom kernels that unlock 10x efficiency -designing novel architectures with researchers and pioneering cutting-edge approaches to mixed-precision training and model parallelism youll have the latest generation hardware at your disposal. This isnt incremental optimization; were pushing the boundaries of whats possible in pre-training at scale where your improvements directly impact live trading.

Other duties as assigned or needed.

Skills Youll Need:

• Expertise and track record of significant measurable performance improvements in large-scale distributed training (MFU throughput convergence cost-per-token).
• Published research in efficient training methods scaling laws architectures or systems for ML
• Background in numerical computing HPC or distributed systems including familiarity with GPUs/TPUs high-performance networking (NVLink/InfiniBand) Kubernetes/Slurm and OS internals
• Expertise in Python and deep experience with modern deep learning frameworks (PyTorch and/or JAX)
• Advanced degree (MS or PhD) in Computer Science Machine Learning Physics Mathematics or a related quantitative field or equivalent industry experience at a frontier lab
• Ability to balance ambitious research goals with practical engineering constraints
• Strong problem-solving skills results orientation and excellent collaborative communication
• Reliable and predictable availability

Bonus Points:

• Expertise in: CUDA kernel development Triton/Pallas/CuTe DSLs PyTorch/JAX internals XLA optimization or hardware acceleration (FPGA/ASIC)
• Knowledge of reinforcement learning post-training or fine-tuning techniques
• Knowledge of financial markets or trading