AI/ML Quant Researcher: Transformer Time‑Series Trading

Next Frontier Capital; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

J.P. Morgan seeks a Quantitative Trading & Research - AI/ML Quantitative Researcher to lead research on transformer-based and time-series foundation models over large-scale market data.

You will develop robust, transferable methods for alpha generation, pricing, market making, execution, and risk management. This role emphasizes deep research under real constraints, with focus on scaling laws, data efficiency, and robustness as core objectives, collaborating with ML infrastructure and trading

Qualifications

• Advanced degree in a quantitative field or equivalent experience.
• Experience pre-training large models from scratch (Transformer/LLM/time-series).
• Experience building large-scale data pipelines and distributed training systems.

Responsibilities

• Pre-train Transformer-based and time-series models from scratch on market data.
• Develop data representations, tokenization, self-supervised objectives, and distributed training recipes.
• Fine-tune models for alpha generation, pricing, market making, execution, and risk management.
• Study scaling laws, cross-instrument transfer, and robustness vs. latency/cost.
• Design evaluation protocols linking pre-training metrics to economic outcomes.

Skills

Large-model training

PyTorch/JAX

Distributed training

Research publications

Education

Advanced degree (MSc/PhD)

Tools

PyTorch

JAX

Job description

J.P. Morgan seeks a Quantitative Trading & Research - AI/ML Quantitative Researcher to lead research on transformer-based and time-series foundation models over large-scale market data.

You will develop robust, transferable methods for alpha generation, pricing, market making, execution, and risk management. This role emphasizes deep research under real constraints, with focus on scaling laws, data efficiency, and robustness as core objectives, collaborating with ML infrastructure and trading