About Voodoo

Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz.

Team

The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile industry. 

Within the Data team, you’ll join the Ad-Network Team which is an autonomous squad of around 30 people.  The team is composed of top-tier software engineers, infrastructure engineers, data engineers, mobile engineers, and data scientists (among which 3 Kaggle Masters). The goal of this team is to provide a way for Voodoo to monetize our inventory directly with advertising partners, and relies on advanced technological solutions to optimize advertising in a real-time bidding environment. It is a strategic topic with significant impact on the business.

The role is France-based but can be full remote.

Role

• Lead the design and architecture of backend services that power real-time model inference and bidding decisions for our OpenRTB platform.

• Collaborate with data scientists and machine learning engineers to deploy, monitor, and optimize ML models that influence real-time bidding strategies, pricing decisions, and targeting.

• Oversee the development of A/B testing frameworks and ensure the seamless integration of experimentation tools into our platform for continuous model and bidding optimization.

• Ensure that all backend services are high-performance, low-latency, and scalable, capable of handling large data volumes (millions of bidding events per second).

• Set best practices for architecture, API design, and distributed systems to ensure robust and maintainable systems at scale.

• Work with the cloud infrastructure teams to ensure efficient deployment, scaling, and monitoring of backend services using Kubernetes, Docker, and CI/CD pipelines.

• Work closely with product managers to define and implement new features, optimizations, and improvements to the bidding and model inference system.

• Lead efforts to optimize performance and cost-efficiency across the backend infrastructure, ensuring that the system can scale effectively with increasing traffic and data.

• Continuously monitor the system’s performance, perform post-deployment analysis, and make improvements based on real-world usage and A/B test results.

Profile

• 5+ years of experience in backend engineering, with a strong focus on designing and building scalable, high-performance systems.

• Extensive experience in distributed systems, microservices, and API design using technologies such as Java, Scala, Python, or Go.

• Expertise in real-time data processing and event-driven architectures (e.g., Kafka, GCP Pub/Sub, Kinesis) for building responsive, low-latency systems.

• Hands-on experience with observability tools (e.g., Prometheus, Grafana, ELK Stack, Datadog) for metrics collection, log aggregation, and system monitoring.

• Deep understanding of A/B testing frameworks and experience integrating them into backend systems for experimentation and optimization.

• Proven ability to design, build, and manage complex cloud infrastructure (AWS, GCP, Azure), including managing services with Kubernetes, Docker, and cloud-native tools.

• Solid experience with CI/CD pipelines, and infrastructure automation tools (e.g., Terraform).

• A focus on building reliable, maintainable, and scalable systems, with experience in performance tuning and cost optimization.

• Excellent problem-solving skills, with the ability to tackle complex technical challenges and provide innovative solutions.

Nice to have

• Experience with OpenRTB and real-time bidding systems.

• Familiarity with machine ****learning and deploying models for inference in production.strategies.

• Exposure to data science workflows and understanding how data engineers and data scientists collaborate in productionizing ML models.

• Contributions to open-source projects or active involvement in technical communities related to backend engineering or machine learning.

Benefits

• Competitive salary upon experience

• Comprehensive relocation package (including visa support)

• Swile Lunch voucher

• Gymlib (100% borne by Voodoo)

• Premium healthcare coverage SideCare, for your family is 100% borne by Voodoo

• Child day care facilities (Les Petits Chaperons rouges)

• Wellness activities in our Paris office

• Unlimited vacation policy

• Remote days