Quant Developer – Live Commodities Trading & ML Infra

Moreton Capital Partners; Ciudad de México; On-site; MXN 900,000 - 1,300,000; Full time

Job summary

Moreton Capital Partners is seeking a Quant Developer to join our team, building data pipelines and LLM-based workflows for research and production. You will enhance backtesting, implement cloud and local ML execution, and productionize signals in a fast-moving capital environment.

You will collaborate with researchers and traders, deploy in AWS/Docker environments, and contribute to research tooling and dashboards while maintaining robust, testable code.”

Qualifications

• Bachelor's in CS/Comp-Eng or computationally heavy subject.
• Ideally a minor in Finance.
• Experience with data engineering and ML workflows is beneficial.

Responsibilities

• Build and maintain data pipelines ingesting futures and alternative datasets.
• Build and improve LLM-based workflows that support research, data processing, and internal tooling.
• Improve backtesting framework (event-driven simulations, realistic slippage/costs, walk-forward validation).
• Support research tooling: feature libraries, experiment tracking, artefact storage.
• Machine learning cloud and local execution and optimization setup.
• Productionize signals into the live trading stack with CI/CD, monitoring, and version control.
• Develop dashboards and alerting for data quality, latency, and model drift.
• Collaborate with researchers to translate hypotheses into robust, testable experiments.

Skills

Python

SQL

Data pipelines

Backtesting

Autonomy

Education

Bachelor's in CS/Comp-Eng or equivalent

Finance minor (preferred)

Tools

Airflow

Snowflake

Pandas

Polars

AWS

Docker

CI/CD

MLflow

Weights & Biases

Git

Job description

Moreton Capital Partners is seeking a Quant Developer to join our team, building data pipelines and LLM-based workflows for research and production. You will enhance backtesting, implement cloud and local ML execution, and productionize signals in a fast-moving capital environment.

You will collaborate with researchers and traders, deploy in AWS/Docker environments, and contribute to research tooling and dashboards while maintaining robust, testable code.”