€110,942.33/yr to €128,010.38/yr
Dublin, Ireland
Permanent, Variable

Machine Learning Engineer

Posted by Harnham - Data & Analytics Recruitment.

Machine Learning Engineer
Product / Tech Company
Dublin
€130,000 - €150,000 + Equity

The Company

Harnham is currently working with a tech company in Dublin that are scaling their machine learning operations rapidly.

Over the last decade they have been building an AI-powered platform for more than 60,000 businesses around the world. Following significant investment into AI there are now a number of positions being recruited for at different levels - AI will be pivotal in helping to shape not just the business, but the industry too!

Their team of Machine Learning Scientists and Engineers dedicate themselves to shipping machine learning into their core products, often working at pace and with cutting-edge algorithms.

Your role will:

  • To deploy machine learning models to production, maintaining/scaling/optimising them
  • Work on improving ML infrastructure, support every stage of the ML pipeline

You:

  • A BSc or MSc in an advanced (machine learning-related) discipline
  • Experience in working in a product company, shipping ML
  • 5 years experience in industry, deploying, maintaining and optimising ML at scale.
  • GenAI / LLM experience is not required
  • Experience working within AWS is required

Here you will be working on some of the toughest engineering problems within machine learning. An aptitude and willingness to learn is critical.

Compensation?

All offers will go through benchmarking, but a range that is possible is between €130,000-€150,000. Equity is on offer at each level. There are regular pay reviews each year.

How to Apply?

Please register your interest by sending your CV via the Apply link on this page. For more information about similar roles, please get in touch with Nick Mandella at Harnham.

Keywords

Python, AWS, GCP, Azure, Machine Learning, Statistics, Artificial Intelligence, Data Scientist, Data Science, deep learning, GenAI, LLMs, MLE, MLOps, Infrastructure.

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