Quantitative Trading AI Scientist: Foundation Models

JPMorgan Chase & Co.; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

JPMorgan Chase & Co. in Singapore seeks an AI/ML quantitative researcher to lead pre-training of Transformer-based and time-series foundation models on large market data.

You will develop data representations, self-supervised objectives, and scalable training pipelines to support alpha generation, pricing, and risk management. The role emphasizes rigorous research under real constraints, with emphasis on performance, transfer across instruments, and collaboration with ML infrastructure engineers

Qualifications

• Master’s, PhD, or equivalent experience in ML, CS, or quantitative field.
• 2+ years of relevant experience.
• Experience pre-training large models from scratch (Transformer/LLM/multimodal/time-series).
• Experience building large-scale data pipelines and distributed training systems using PyTorch, JAX, or equivalent frameworks.
• Deep knowledge of large-model training and evaluation: optimization, parallelism, mixed precision, checkpointing, experiments.
• Evidence of research quality through publications, open-source systems, or production deployment.

Responsibilities

• Pre-train Transformer-based and time-series foundation models from scratch using large-scale market data.
• Develop data representations, tokenization, self-supervised objectives, model architectures, and distributed training recipes.
• Fine-tune and post-train models for alpha generation, pricing, market making, execution, and risk-management tasks.
• Study scaling laws, transfer across instruments and regimes, data efficiency, and trade-offs among model quality and latency.
• Design evaluation protocols linking pre-training metrics to economically meaningful outcomes, including out-of-sample prediction and simulated trading.
• Build reusable training, checkpointing, evaluation, and model-serving components with ML infra engineers.

Skills

ML research

Transformer training

Time-series modeling

Distributed training

Education

Advanced degree

Tools

PyTorch

JAX

Job description

JPMorgan Chase & Co. in Singapore seeks an AI/ML quantitative researcher to lead pre-training of Transformer-based and time-series foundation models on large market data.

You will develop data representations, self-supervised objectives, and scalable training pipelines to support alpha generation, pricing, and risk management. The role emphasizes rigorous research under real constraints, with emphasis on performance, transfer across instruments, and collaboration with ML infrastructure engineers