Staff Machine Learning Engineer

4 weeks ago

Dublin, Ireland Harnham Full time

This range is provided by Harnham.
Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Direct message the job poster from Harnham
Up to €135,000 + Benefits
About the Role
Our client, one of the top players in the gaming/entertainment space, is seeking a
Staff Machine Learning Engineer
to join their Pricing/forecasting team based in Dublin.
This role sits at the heart of how they deliver meaningful pricing strategies across global markets - influencing both revenue and player experience at scale.
You'll be working on a strategically backed project that has full executive sponsorship, providing pricing recommendations that directly impact hundreds of millions of players and some of the world's most recognisable gaming studios.
Key Responsibilities
Design and implement advanced ML models to predict demand, price elasticity, and product cannibalisation.
Build forecasting algorithms and optimisation workflows (using tools like OR-Tools) to balance growth with commercial constraints.
Develop clustering strategies to enable smarter pricing and promotional decisions.
Lead the full machine learning development cycle — from feature engineering through to deployment, testing, and monitoring.
Work with cross-functional teams in Engineering, Product and Business to translate real-world problems into scalable, ML-powered solutions.
Mentor junior ML engineers and play a key role in shaping the technical direction of the team.
Contribute to the broader ML strategy, including tooling, architecture, and roadmap planning.
What You'll Bring
A Master's or PhD in a relevant discipline (Computer Science, Statistics, Econometrics, Operations Research, etc.).
Experience leading ML product development in a commercial setting, with a focus on forecasting, pricing.
3-5 years of industry experience
Strong understanding of time-series modelling, constraint solving, and pricing systems.
Proven ability to deliver high-scale ML systems from idea to production in complex environments.
Exceptional communication skills - able to translate complex ML outputs into meaningful business outcomes.
Previous exposure to revenue management, recommender systems, or experimentation frameworks (A/B testing, uplift modelling).
Familiarity with modern ML infrastructure: Databricks, Snowflake, Tecton, and cloud-based CI/CD tooling.
A background in digital goods, e-commerce, or the gaming industry is a plus.
Contributions to the ML community via publications, open-source, or conference talks.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering, Science, and Analyst
Industries
Computer Games
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