Quant Platform Engineer: ML Pipelines & Distributed Compute

Millennium; Dublin; On-site; EUR 120,000 - 180,000; Full time

Job summary

Millennium is seeking an experienced software engineer to extend a distributed dataset API and build large-scale ML pipelines. You will work across research and platform teams to improve compute, storage, and model lifecycle in a production environment.

The role emphasizes strong Python skills, modern CI/CD practices, and collaboration with researchers to shape the platform’s evolution in a finance-focused setting.

Qualifications

• 6+ years of Python and distributed systems experience in a quantitative finance environment.
• Bachelor’s degree in Computer Science, Mathematics, Financial Engineering, Operations Research, or related field.
• Deep knowledge of distributed compute frameworks such as Ray, Dask, Spark, PySpark or Slurm.
• Hands-on ML/DL workflows using PyTorch and XGBoost across training and serving lifecycles.
• Strong Python skills and Git/Unix/Linux/Bash with modern CI/CD workflows.
• Experience with kdb+, PyKX, Polars, Arrow, and cloud tooling is a plus.

Responsibilities

• Extend a distributed dataset API with new operators and optimizations for a smooth user experience.
• Design and implement ML pipelines for large-scale training, tuning, and model serving.
• Improve reliability, observability, and multi-user capabilities of the compute stack.
• Build durable abstractions to keep the platform flexible as compute backends evolve.
• Write, test, document, and maintain code with CI/CD and automation.
• Collaborate with researchers and engineers on platform direction and architecture.

Skills

Python

Distributed systems

Communication skills

Quantitative finance domain knowledge

Education

Bachelor's degree in Computer Science, Mathematics, Financial Engineering, Operations Research, or related field

Tools

Ray

Dask

Spark

PySpark

Slurm

PyTorch

XGBoost

Git

Unix/Linux

Bash

Kubernetes

Polars

Arrow

kdb+

PyKX

Job description

Millennium is seeking an experienced software engineer to extend a distributed dataset API and build large-scale ML pipelines. You will work across research and platform teams to improve compute, storage, and model lifecycle in a production environment.

The role emphasizes strong Python skills, modern CI/CD practices, and collaboration with researchers to shape the platform’s evolution in a finance-focused setting.