Find Engineer ml platform Jobs in Dublin, D

Quantitative Developer – Compute & ML Platform
Millennium Management —Dublin, County Dublin
- Computer Science
- Research
- Bachelor's degree
2h
Sr Machine Learning Engineer
paypal —Dublin, County Dublin
- Full-time
- Azure
- Engineering
- Java
- Annual leave
Lead Security Engineer
JPMorganChase —DUBLIN 2, County Dublin
- Full-time
- DevOps
- AWS
- Analysis skills
2d
Partner Solutions Architect
Nebius —Dublin, County Dublin
- Remote
- Azure
- AWS
- AI
Quick apply
11d
Director of Data Engineering
2K —Dublin, County Dublin
- DevOps
- Data analysis skills
- AI
Quick apply
AI Architect (R-18541)
Dun & Bradstreet —Dublin, County Dublin
- Full-time
- Hybrid work
- Azure
- Computer Science
- DevOps
- Annual leave
Quick apply
Senior Software Engineer, Cash Forecasting
Ripple —Dublin, County Dublin
- Full-time
- Azure
- Oracle
- AWS
Quick apply
7d
Staff AI Designer
Intercom —Dublin, County Dublin
- Hybrid work
- Annual leave
- Work from home
Senior Sales Operations Analyst
MongoDB —Dublin, County Dublin
- Hybrid work
- Azure
- Sales
- SQL
Senior Data Scientist
Verve —Dublin, County Dublin
- Doctoral degree
- Master's degree
- SQL

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Quantitative Developer – Compute & ML Platform

Millennium Management -
Dublin, County Dublin

Apply Now

Job details

2 hours ago

Qualifications

CI/CD
Computer Science
Kubernetes
Spark
UNIX
Git
Research
Bash (Unix shell)
Bachelor's degree
Distributed systems
Linux
Communication skills
Python

Full job description

Quantitative Developer – Compute & ML Platform

About Millennium
Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.

Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact.

Meet the Team
The Execution Services team supports trading across products and geographies, with a focus on execution quality, trading efficiency, and the tools that help portfolio managers make informed decisions. Within this group, Central Liquidity Strategies develops and operates trading capabilities that support internal liquidity solutions across the platform. The team works across quantitative research, platform engineering, and production systems to build the compute, storage, and model infrastructure that supports research and live trading.

What You'll Do

Extend the proprietary distributed dataset API, a Polars-style, lazily evaluated, DAG-planned DataFrame surface, with new operators, optimizations, and a strong new-user experience
Design and implement machine learning pipelines spanning large-scale training and tuning, model serving, production validation, and the full retraining lifecycle for a growing model fleet
Improve the reliability, observability, and multi-user capabilities of the compute infrastructure, including resource management, workload isolation, and clean backend interfaces
Build durable abstractions that allow the platform to remain flexible as distributed compute backends evolve
Write, support, maintain, and test code using strong engineering practices, including unit testing, documentation, automation, and CI/CD workflows
Partner with team members on the direction, design, and architecture of the platform
Collaborate closely with researchers and platform engineers to align compute and storage capabilities across the environment

What You Bring

6+ years of Python and distributed systems experience in a quantitative finance environment, with a strong track record of building platform abstractions used by others in production
Bachelor’s degree in Computer Science, Mathematics, Financial Engineering, Operations Research, or a related field
Deep working knowledge of one or more distributed compute frameworks such as Ray, Dask, Spark, PySpark, or Slurm, with a clear understanding of their tradeoffs
Hands-on experience implementing machine learning and deep learning workflows using tools such as PyTorch and XGBoost, with comfort across the full training-to-serving lifecycle
Strong Python skills, and optionally kdb+, for platform and research-focused development
Strong working knowledge of Git, Unix/Linux, Bash, and modern CI/CD workflows
Strong communication skills and the ability to work effectively in a collaborative team environment
Experience with kdb+, PyKX, Polars, Arrow, columnar or lazy query engines, cash equities, live analytics, and/or cloud tooling including Kubernetes is a plus

Apply Now

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engineer ml platform jobs in dublin, d

Quantitative Developer – Compute & ML Platform

Sr Machine Learning Engineer

Lead Security Engineer

Partner Solutions Architect

Director of Data Engineering

AI Architect (R-18541)

Senior Software Engineer, Cash Forecasting

Staff AI Designer

Senior Sales Operations Analyst

Senior Data Scientist

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