Overview

Si sus habilidades, experiencia y cualificaciones coinciden con las de esta descripción del puesto, no demore su solicitud.

In this role you will architect and evolve Preply’s ML platform to move research into production at scale. You’ll design cloud-native systems for distributed training and inference, with strong emphasis on observability, testing, and cost-efficiency. You will partner with ML leads and engineers to set standards, enable experimentation, and deliver modular, measurable ML services. This position offers impact across product teams and a chance to shape the future of a global learning platform.

Compensaciones / Incentivos

- lesson allowance (monthly)
- Learning & Development budget
- time off for self-development
- equity
- health insurance
- mental health support platforms

Responsabilidades

- Design and implement the ML platform architecture (experiment tracking, artifact management, scalable deployment)
- Build cloud-native distributed training and inference solutions with GPU support and autoscaling
- Own CI/CD for ML, including testing, validation, and performance checks
- Embed observability across ML workflows (metrics, alerts,



drift detection, lineage)
- Mentor engineers, influence standards, and reduce risk in complex decisions
- Align platform direction with experimentation velocity, cost-efficiency, and user impact
- Develop modular, testable ML services with monitoring from day one
- Contribute to LLM platform capabilities (RAG pipelines, latency-optimized inference, prompt experimentation frameworks)

Requisitos principales

- 8+ years of engineering experience in large-scale Data/ML platforms
- Deep knowledge of cloud services and end-to-end xugodme ML workflows (versioning, monitoring, performance benchmarking)
- Experience collaborating with scientists and building enabling tools
- Excellent communication and cross-functional influence; mentoring ML engineers
- Familiarity with LLM frameworks (LangChain, LlamaIndex), vector stores, and retrieval infrastructure

- communication and influence
- mentoring and coaching
- cross-functional collaboration
- cloud-native ML platform design
- distributed training and inference on cloud
- CI/CD for ML

📌 Staff Machine Learning Ops Engineer - barcelona
🏢 Jobrapido
📍 Barcelona