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Machine Learning Engineer - Pricing

Posted Yesterday
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In-Office
Dublin
Junior
In-Office
Dublin
Junior
As a Mid-Level Machine Learning Engineer, you will develop ML models for pricing, refine forecasting algorithms, and optimize promotion strategies, collaborating across teams to enhance user experiences at PlayStation.
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Why PlayStation?

PlayStation isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The PlayStation family of products and services including PlayStation®5, PlayStation®4, PlayStation®VR, PlayStation®Plus, acclaimed PlayStation software titles from PlayStation Studios, and more.

PlayStation also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.

The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation.

Mid-Level Machine Learning Engineer - Pricing

Do you want to join a Machine Learning team committed to enhancing the PlayStation experience for hundreds of millions of users and also game studios? The work we do delivers highly impactful pricing recommendations to our studios and has strong leadership sponsorship. The Machine Learning Engineers within the DTIS group will deliver optimized interactions across PlayStation experiences by designing, coding, training, documenting, cost-effectively deploying, and evaluating business-critical machine learning and AI systems.

We are looking for someone who can architect and build delightful production-grade products for customer-facing experiences, in an agile environment, collaborating with teams across Engineering, Product and Business. You will work on a project backed by executive leadership and poised to significantly influence revenue and user engagement.

You Will:
  • Build and maintain ML models that quantify product price-elasticity and cannibalization effect to support multi-period promotions.
  • Refine time-series forecasting algorithms to predict demand across multiple regions and product lines.
  • Develop optimization workflows (OR-Tools) that balance sales growth and business constraints.
  • Refine clustering algorithms to identify lookalike products for smarter pricing and promotional strategies.
  • Apply a broad spectrum of state-of-the-art machine learning and deep learning technologies in the areas of classification, regression, clustering, time series forecasting, uplift modeling, and synthetic data generation.
  • Build scalable and resilient ML systems along with appropriate monitoring and continuous evaluation frameworks.
  • Work closely with cross-functional partners in business and product to translate requirements into effective, scalable, ML-driven solutions.
  • Collaborate with other engineering functions in Client, Server, and QA to drive ML integrations and deliver results.
  • Collaborate with ML application teams that power product personalizations and search to further enhance the core experiences of our players. 
You Bring:
  • Advanced degree (Master’s or Ph.D.) in CS/Statistics/Data Science/Operations Research/Econometrics, specializing in machine learning and optimization problems.
  • 1+ years of industry experience applying time-series models in production, with hands-on experience in forecasting libraries (e.g. with LightGBM, Prophet).
  • Proven track record with mixed-integer programming or constraint solvers for pricing or resource allocation.
  • Strong programming skills in Python, Java, with proficiency in ML libraries and frameworks like TensorFlow, PyTorch, Spark Mlib, and scikit-learn
  • Good ML systems engineering experience (such as job orchestration, training pipelines, deployment, serving, monitoring).
  • Expertise in measuring the performance unsupervised and supervised models.
  • Proven record of successfully delivering commercial machine learning products from conception to production.
  • Experience with software engineering principles, modern ML tech stacks, and use of Databricks, Tecton, Snowflake, and cloud services like AWS for machine learning development and deployment.
Preferred Qualifications:
  • Previously worked with revenue-management systems.
  • Experience in a variety of machine learning and AI techniques, such as forecasting models, constraint optimization, classification models on structured data, clustering, and other supervised and unsupervised learning models.
  • Experience working in fast-paced environments, on business-critical missions.
  • Good communication skills and the ability to convey complex ML concepts to a non-ML audience.
  • Experience in e-commerce, digital goods, or gaming industries.
  • Experience with recommender systems and similarity matching algorithms.
  • Background in experimentation design, causal inference, uplift modeling, online A/B testing frameworks, and relevant metrics.
  • Experience with large-scale structured data manipulation and processing. 
  • Experience working with custom ML platforms for continuous integration, deployment, and monitoring of machine learning models.

Equal Opportunity Statement:

Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.

We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. 

PlayStation is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Top Skills

AWS
Databricks
Java
Lightgbm
Prophet
Python
PyTorch
Scikit-Learn
Snowflake
Spark Mlib
Tecton
TensorFlow

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