Quantitative Trading & Research - AI Scientist, Quantitative Research - Associate

JPMorganChase; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

J.P. Morgan's AI Market Lab in Singapore seeks an AI/ML quantitative researcher to build Transformer-based and time-series foundation models for trading across FX, rates, commodities, and equities.

You will work on pre-training from scratch, rigorous evaluation, and deployment within a fast-paced research-to-production pipeline. You should have a strong research background, hands-on model training experience, and the ability to operate under real-market constraints, including latency and data

Qualifications

• Advanced degree in ML, CS, or quantitative field.
• At least 2 years of hands-on relevant experience.
• Experience pre-training a large model from scratch.
• Experience with PyTorch or JAX and distributed training.
• Proven research quality through publications or deployments.

Responsibilities

• Pre-train Transformer- and time-series foundation models from scratch on large market datasets.
• Develop data representations, tokenization, self-supervised objectives, and distributed training.
• Fine-tune models for alpha, pricing, market making, execution, and risk management.
• Study scaling laws, cross-instrument transfer, regime robustness, data efficiency, latency trade-offs.
• Design evaluation protocols linking pre-training metrics to live trading outcomes.
• Collaborate with ML infra engineers to build training, checkpointing, and model serving tools.

Skills

Advanced degree

2+ years experience

Pre-training large models

PyTorch

JAX

Distributed training

Education

Master's or PhD

Tools

PyTorch

JAX

Job description

Job Description

The Quantitative Trading & Research (QTR) group is responsible for systematic trading across FX, Rates, Commodities, Credit, Equity and a wide range of markets. Within QTR, AI Market Lab brings together quantitative research, modern artificial intelligence, market microstructure, and high-performance engineering to develop the next generation of electronic trading capabilities. Our work spans signal research, pricing, market making, execution, portfolio construction, risk management, and the production systems that support them.

We are seeking an AI/ML quantitative researcher with hands-on experience pre-training large foundation models from scratch. You will lead research on building Transformer-based and time-series foundation models over large-scale market datasets, and develop the methods needed to make them robust, transferable, and measurable across instruments and regimes.

This role is designed for someone who wants to do deep research with real constraints—where questions like scaling laws, data efficiency, and robustness are not academic footnotes, but the core of the agenda.

Job Responsibilities

• Pre-train Transformer-based and time-series foundation models from scratch using large-scale market, order-book, transaction, and cross-asset datasets.
• Develop data representations, tokenization schemes, self-supervised objectives, model architectures, and distributed training recipes for financial time series.
• 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.

Required Qualifications

• Advanced degree (Master's, PhD, or equivalent experience) in machine learning, computer science, statistics, mathematics, operations research, engineering, or a related quantitative field.
• At least 2 years of relevant experience
• Demonstrated experience pre-training a large model from scratch (Transformer/LLM/multimodal/time-series). Experience limited to API usage or prompt engineering is not sufficient.
• 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, experiment design, ablations, and benchmarking.
• Evidence of research/technical quality through successful large-model training, high-impact research, open-source systems, or production deployment.

Preferred Qualifications

• Experience with fine-tuning/post-training for forecasting, ranking, decision-making, or structured prediction.
• Prior work on time-series foundation models, limit-order-book modeling, multimodal market data, or cross-asset transfer learning.
• Experience in quantitative trading, HFT, electronic market making, or systematic investing—especially with models deployed to live trading.
• Publications at leading ML venues and/or substantial contributions to large-scale model-training systems.

ABOUT US

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

About The Team

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.