Engineering Manager, Machine Learning

Engineering Manager, Machine Learning

Do you want to lead a team building advanced decision systems that directly shape monetisation strategies across the PlayStation ecosystem? Are you passionate about combining machine learning and operational research to solve complex, high-impact business problems at scale? We are building systems that power decisions across a global catalogue of games, including base pricing across lifecycle stages of a game, while balancing revenue growth, player experience, and cannibalisation across titles.

We are looking for an experienced Machine Learning Engineering Manager to lead a hybrid team of Machine Learning engineers and Operations Research experts. You will work on high-impact, executive-visible initiatives, partnering closely with Product, Business, and Engineering teams to translate complex, ambiguous problems into scalable, production-ready systems.

What You’ll Do

Lead and grow a team of machine learning engineers and optimisation specialists, fostering collaboration across disciplines and raising the bar for technical excellence.

Build a high-performing, inclusive team by:

• Coaching and developing engineers across ML and OR disciplines
• Providing clear feedback, career growth, and performance management
• Hiring and retaining top talent

Improve large-scale optimisation systems that:

• Incorporate predictive signals from machine learning models (e.g., demand forecasting, item elasticity).
  
  
• Leverage optimisation frameworks using Gurobi to make decision recommendations under known business constraints.

Partner closely with Product, Business, and regional stakeholders to:

• Translate business goals and constraints into optimisation frameworks.
  
  
• Align on tradeoffs between short-term performance and long-term strategy.
  
  
• Resolve conflicting priorities through data-driven decision-making.

Ensure systems are explainable, trustworthy, and actionable by:

• Providing clear reasoning behind model-recommended decisions.
  
  
• Enabling debugging and traceability across ML and optimisation components.
  
  
• Driving adoption with business and product stakeholders.

You Bring:

• Deep understanding of the relevant ML and OR domains and infrastructure with a track record of delivering complex ML and OR systems into production.
• Proven strong experience leading and developing high-performing ML and OR teams, including: Growing engineers across different skill sets (Machine Learning, ML Infra, Operational Research); Driving career growth and performance evaluation; Hiring and retaining high-performing teams.
• Demonstrated ability to create a strong team culture with high accountability, creativity and continuous improvement.
• Ability to provide technical direction at the architecture level while fostering pragmatic, high-quality, high-velocity execution.
• Demonstrated success driving cross-functional initiatives that require influencing without direct authority, in fast-moving environments
• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

• MS, or PhD in Computer Science, Machine Learning, Operational Research

 

Preferred Q