Machine Learning Engineer

Ambition Needs a Place to Grow.

At Playtika, we create mobile games enjoyed by millions worldwide.

Combining the scale of a public company (NASDAQ: PLTK) with the speed and ownership of a startup, we are a global leader where innovation, data, and creativity shape the future of entertainment.

Here, your ideas matter, your decisions impact products, and your growth is supported across global studios.

Bring your hunger where it belongs: at the front of the pack.

Playtika is looking for a Senior Machine Learning Engineer to join our team and build efficient, data-driven AI systems that power our core personalization infrastructure. The ideal candidate has a strong backend engineering background and proven experience designing, deploying, and maintaining high-throughput machine learning architectures using Python.

Responsibilities: 

• Design, build, and maintain large-scale ML serving architectures for real-time personalization or other AI systems, impacting millions of users.


• Transform complex data science prototypes into resilient, production-ready infrastructure, and integrate algorithms and GenAI models into production environments.


• Develop robust streaming pipelines to support continuous model inference and training workflows.


• Develop and maintain AI agents and internal tooling to empower AI-driven development workflows and modern workspaces.


• Implement end-to-end observability, tracing, and alerting for production ML systems.


• Collaborate closely with data scientists, product managers, architects, and cross-functional engineering teams.


• Stay up to date with machine learning, serving frameworks, and GenAI developments across the industry.

Requirements: 

• BSc or MSc in Computer Science, Engineering, or a related technical field.


• 5+ years of experience as an ML Engineer, Backend Engineer, or similar, with a track record of delivering scalable production solutions.


• High proficiency in Python and modern API development (FastAPI, Pydantic).


• Hands-on experience with streaming and data processing workloads (Apache Kafka, PySpark, Airflow/MLflow/Kubeflow).


• Experience deploying containerized applications (Docker, Kubernetes) and utilizing model serving frameworks.


• A highly self-driven autodidact who is passionate about adopting innovative technologies.


• A team player who thrives in strategic projects, actively participates in decision-making, and collaborates effectively with business and technical functions.


• Big Advantage: Real-world production experience with personalization architectures, recommendation systems, or Reinforcement Learning models.