Research Engineer, Pre-Training

About the role

As a Pre-Training Research Engineer, you'll be at the forefront of developing massive-scale foundation models that fundamentally transform how we understand and predict markets. You'll 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 gains. Co-designing novel architectures with researchers and pioneering cutting-edge approaches to mixed-precision training and model parallelism, you'll have the latest generation hardware at your disposal. This isn't incremental optimization; we're pushing the boundaries of what's possible in pre-training at scale, where your improvements directly impact live trading.

Responsibilities

• Build fault-tolerant infrastructure that scales across thousands of GPUs and TPUs with near-linear performance
• Engineer data pipelines that stream terabytes per second as models train on petabytes of data from global markets
• Design custom kernels that unlock 10x efficiency gains
• Co-design novel architectures with researchers
• Pioneer cutting-edge approaches to mixed-precision training and model parallelism
• Other duties as assigned or needed

Qualifications

• 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

Skills

• 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

Benefits

• Discretionary bonus eligibility
• Medical, dental, and vision insurance
• HSA, FSA, and Dependent Care options
• Employer Paid Group Term Life and AD&D Insurance
• Voluntary Life & AD&D insurance
• Paid vacation plus paid holidays
• Retirement plan with employer match
• Paid parental leave
• Wellness Programs

Pay

Annual Base Salary Range: $300,000 USD - $350,000 USD