Senior MLOps Engineer

Job title: Senior MLOps Engineer

About the Role

At Turo, data is at the core of how we manage our marketplace. We are looking for a Senior MLOps Engineer to design and evolve our ML platform that sits at the heart of the product. You will collaborate with Data Science and ML Engineering teams to build and maintain high-performance ML pipelines, from feature creation to model deployment, and develop infrastructure for large-scale training, tuning, and serving.

What You'll Do

• Play a central role in creating and optimizing our machine learning and AI platform.
• Collaborate with Data Science and Machine Learning Engineering teams to build and maintain high-performance ML pipelines, from feature creation to model deployment.
• Develop optimized infrastructure for large-scale model training, tuning, and serving.
• Select and integrate the best tools for each stage of the ML lifecycle (orchestration, feature store, distributed computing, artifact registry, etc.).
• Leverage OSS ecosystem technologies (mainly Ray, MLFlow, Airflow, Docker, Kubernetes).
• Improve batch and real-time processing systems, ensuring robust, maintainable code.
• Mentor and support the team by fostering a culture of excellence and continuous learning.

What We're Looking For

• 5+ years of industry experience.
• Strong background in development and infrastructure.
• Experience setting up and scaling ML training, testing, and production pipelines.
• Proficiency in Python programming.
• Experience with Java or Kotlin is a plus.
• Familiarity with Infrastructure-as-Code (IaC) tools such as Terraform.
• Knowledge of Kubernetes, Airflow, and distributed systems.
• Understanding of statistical methods, optimization techniques, and machine learning algorithms.
• Enthusiastic and ready to innovate; comfortable communicating in English for recruitment.

Compensation & Benefits

• Salary: 70,000–87,000 EUR per year at the Paris office (base).
• Equity grants and social benefits.
• Hybrid work: in-office three days per week (Mondays, Wednesdays and Thursdays) with partial remote option.
• Accessibility: position eligible for people with disabilities.
• Note: Salary ranges reflect market targets; actual compensation determined by skills, experience, and education.