greenhouse
Research Engineer, Pre-Training
Jump Trading
Chicago, USA
Full-time
Senior
Onsite
USD 300000-350000 yearly / year
Discovered 2 weeks ago
GPUsTPUsNVLinkInfiniBandKubernetesSlurm
Free
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GPUsTPUsNVLinkInfiniBandKubernetesSlurm
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What You'll Do
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, where milliseconds matter and no playbook exists. 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
Skills You'll 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
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