ML Platform Engineer

Trade Republic; Paris; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Trade Republic in Paris is hiring for a senior infrastructure engineer to build and own production-grade systems for real-time ML, feature serving, and critical decisioning.

You will design data-intensive platforms processing high-volume streams with sub-second latency, define reusable patterns, and collaborate with ML, data, backend and product teams while mentoring peers to raise engineering ownership.

Qualifications

• Experience with building and operating production-grade services on Kubernetes.
• Strong understanding of distributed systems and networking, latency, reliability.
• Ability to translate ambiguous requirements into simple, reliable platform capabilities.

Responsabilités

• Build and own production-grade infrastructure for real-time ML, feature serving, and critical decisioning systems.
• Design data-intensive platforms that process high-volume event streams with low latency and strong reliability.
• Define reusable engineering patterns that help teams build, ship, operate, and scale platform capabilities reliably.
• Build and operate data streaming and serving platforms for sub-second algorithms in mission-critical systems.
• Mentor peers, share knowledge, and help raise the quality of engineering ownership across the team.

Connaissances

Distributed systems

Latency optimization

Reliability engineering

Autonomy

Mentoring

Outils

Kubernetes

ClickHouse

Kafka

Flink

Description du poste

• We have a bold mission to empower everyone to build wealth with easy, safe, and free access to financial systems. You will have the opportunity to grow your career by collaborating with a team of outstanding talents and state-of-the-art technology to build a lasting, positive future for millions
• Build and own production-grade infrastructure for real-time ML, feature serving, and critical decisioning systems
• Design data-intensive platforms that process high-volume event streams with low latency and strong reliability
• Define reusable engineering patterns that help teams build, ship, operate, and scale platform capabilities reliably
• Build and operate data streaming and serving platforms for sub-second algorithms in mission-critical systems
• Work closely with ML, data, backend, and product teams to turn complex requirements into simple, reliable systems
• Mentor peers, share knowledge, and help raise the quality of engineering ownership across the team

Nice to have: experience with ClickHouse, Kafka, Flink, or similar technologies for stream processing and high-performance SQL workload Able to work across infrastructure, data, backend, and ML systems, translating ambiguous requirements into simple, reliable platform capabilities Solid understanding of distributed systems, networking, latency, reliability, backpressure, and operational trade-offs. Ability to make pragmatic trade-offs across performance, scalability, cost, and reliability in large-scale production systems Strong interpersonal skills, self-starter with high autonomy, and a focus on knowledge sharing and team growth Strong background in software, systems, or infrastructure engineering, with hands-on experience building and operating production-grade services on Kubernetes