Senior Rust Engineer - Real-Time ML Backend (Remote-Friendly)

Appodeal; Barcelona; Presencial; EUR 90.000 - 130.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary

Flexible work arrangements

Career growth opportunities

Professional development

Descripción de la vacante

Appodeal is seeking a Senior Rust Engineer to join our Barcelona team and help build high-performance, real-time backend systems powering our ML-driven AdTech platform. You will work on core infrastructure, feature stores, identity services, and custom inference layers to ensure scalability and reliability.

The role emphasizes low-latency, high-load processing, collaboration with ML and data teams, and ongoing improvements to architecture and observability.

Formación

• 5+ years of experience in software engineering.
• Strong proficiency in Rust (or transition from C/C++/Zig to Rust).
• Experience designing and building high-load, performance-critical systems.
• Solid understanding of system design, concurrency, and performance optimization.
• Basic knowledge of machine learning workflows and tools.

Responsabilidades

• Contribute to the development of real-time applications and ML platform components.
• Build and maintain high-load, low-latency backend services.
• Work on in-house solutions including feature stores, user identity services, and a custom inference layer.
• Optimize system performance across on-premise Docker & Kubernetes environments.
• Collaborate with ML, data, and engineering teams to support production ML systems.
• Continuously improve system architecture, observability, and efficiency.

Conocimientos

Rust

System design

High-load systems

Concurrency

Performance optimization

Herramientas

Docker

Kubernetes

GitHub

Descripción del empleo

Appodeal is seeking a Senior Rust Engineer to join our Barcelona team and help build high-performance, real-time backend systems powering our ML-driven AdTech platform. You will work on core infrastructure, feature stores, identity services, and custom inference layers to ensure scalability and reliability.

The role emphasizes low-latency, high-load processing, collaboration with ML and data teams, and ongoing improvements to architecture and observability.