Senior ML Engineer

Role Overview

• You will integrate a small, high-ownership squad where you own the full lifecycle
• design, implement, deploy, monitor, and iterate
• with direct impact on revenue-critical systems processing millions of bid requests per second.
• 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
• including potentially developing proprietary models in-house.
• 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.

Requirements

• 7+ years of experience in backend engineering, with a strong focus on designing and building scalable, high-performance systems.
• Well-versed with machine learning and deploying models for inference in production.
• Extensive experience in distributed systems, microservices, and API design using Python.
• Hands-on experience with observability tools (e.g., Prometheus, Grafana) for metrics collection, log aggregation, and system monitoring.
• Understanding of A/B testing concept and experience integrating them into backend systems for experimentation and optimization.
• Proven ability to design, build, and manage cloud infrastructure using Kubernetes, Docker, and cloud-native tooling. Experience with other cloud providers is welcome, but AWS is preferred as it is our primary platform.
• 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.
• Strong problem-solving skills, quality ownership and autonomy: able to take a task from design to production end-to-end
• writing contract tests for upstream/downstream interfaces, verifying changes in staging, and treating CI as necessary but not sufficient.

Tech Stack

• AWS
• Cloud
• Distributed Systems
• Docker
• Grafana
• Kubernetes
• Microservices
• Prometheus
• Python
• Terraform

Benefits

• Competitive salary upon experience
• 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
• Remote days