AI/ML Quant Researcher: Market-Focused Foundation Models

J.P. Morgan; Worcester (MA); On-site; USD 150,000 - 230,000; Full time

Job summary

J.P. Morgan seeks an AI/ML quantitative researcher to lead pre-training of large foundation models from scratch, focusing on Transformer-based and time-series models over expansive market data. You will shape representations, objectives, and architectures for robust and transferable models across instruments.

The role emphasizes real-world constraints, scalable training, and collaboration with ML infra engineers to deploy models for alpha generation, pricing, and risk tasks.

Qualifications

• Advanced degree in a quantitative field.
• Proven experience pre-training large models from scratch.
• Experience building large-scale data pipelines and distributed training systems.

Responsibilities

• Pre-train Transformer-based and time-series models on market data.
• Develop data representations and training objectives for financial time series.
• Fine-tune models for alpha generation, pricing, and risk tasks.
• Study scaling laws and data efficiency across instruments.
• Design evaluation protocols linking pre-training to trading outcomes.
• Collaborate with ML infra engineers on tooling and deployment.

Skills

Transformer pre-training

Time-series modeling

PyTorch

JAX

Distributed training

Large-model training

Education

Master’s or PhD in ML/CS

Tools

PyTorch

JAX

Experiment tooling

Large-scale data pipelines

Job description

J.P. Morgan seeks an AI/ML quantitative researcher to lead pre-training of large foundation models from scratch, focusing on Transformer-based and time-series models over expansive market data. You will shape representations, objectives, and architectures for robust and transferable models across instruments.

The role emphasizes real-world constraints, scalable training, and collaboration with ML infra engineers to deploy models for alpha generation, pricing, and risk tasks.