AI Quant Research Scientist-Trading & Markets (Associate)

Fairygodboss; New York (NY); On-site; USD 180,000 - 260,000; Full time

Job summary

JPMorgan Chase & Co. in New York seeks an AI/ML quantitative researcher at Associate or VP level to lead pre-training of Transformer-based and time-series foundation models from scratch on large market datasets.

You will design data representations, distributed training recipes, and evaluation protocols to connect pre-training metrics to trading outcomes with emphasis on robustness, scalability, and cross-asset transfer.

Qualifications

• Advanced degree in a quantitative field (ML/CS/Statistics/Math/OR/Engineering) or equivalent experience.
• Experience pre-training a large model from scratch (Transformer/LLM/time-series).
• Experience building large-scale data pipelines and distributed training with PyTorch or JAX.
• Deep knowledge of large-model training, optimization, parallelism, mixed precision, checkpointing, experiment design, ablations, and benchmarking.
• Evidence of research quality through successful large-model training, high-impact research, open-source systems, or production deployments.

Responsibilities

• Pre-train Transformer-based and time-series foundation models from scratch on market data.
• Develop data representations, tokenization schemes, self-supervised objectives, model architectures, and distributed training recipes.
• Fine-tune and post-train foundation models for alpha generation, pricing, market making, execution, and risk-management tasks.
• Study scaling laws, transfer across instruments and asset classes, regime robustness, data efficiency, and the trade-offs among model quality, inference cost, and latency.
• Design evaluation protocols that connect pre-training metrics to economically meaningful outcomes, including out-of-sample prediction, simulated trading, transaction costs, capacity, and live markouts.
• Build reusable training, checkpointing, evaluation, and model-serving components with ML infrastructure engineers.

Skills

Pre-training large model from scratch

Distributed training systems

Model optimization & benchmarking

Transformer/LLM/time-series

Education

Advanced degree in ML/CS/Statistics/Math/OR/Engineering

Tools

PyTorch

JAX

Job description

JPMorgan Chase & Co. in New York seeks an AI/ML quantitative researcher at Associate or VP level to lead pre-training of Transformer-based and time-series foundation models from scratch on large market datasets.

You will design data representations, distributed training recipes, and evaluation protocols to connect pre-training metrics to trading outcomes with emphasis on robustness, scalability, and cross-asset transfer.