Hybrid AI/ML Engineer — Build Production-Ready Pipelines

Aimlroles

Madrid

Hybrid

EUR 60,000 - 90,000

Full time

14 days+
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Job summary

Aily Labs in Madrid is hiring a MID AI/ML Engineer to build and scale AI/ML infrastructure powering our decision intelligence platform. You will implement end-to-end ML pipelines, optimize deployments, and collaborate with data scientists and software engineers to ship reliable systems.

The role emphasizes production-ready models, robust APIs, and cloud-based scaling, with a hybrid work policy (2 days in the office).

Qualifications

  • Solid AI/ML fundamentals.
  • Strong Python programming skills.
  • Experience with APIs, Kubernetes, Docker and cloud services.
  • Mentor junior team members on technical topics.

Responsibilities

  • Contribute to building and maintaining ML systems and pipelines (data → model → deployment → monitoring) with guidance from mid/senior engineers.
  • Support productization of AI/ML models and LLMs by working on APIs, infrastructure, and applying software engineering best practices (testing, CI/CD, versioning).
  • Collaborate with data scientists and engineers to deliver scalable solutions, monitor systems in production, and communicate progress and technical challenges.
  • Partner with Data Scientists and Engineers to bring AI solutions to production.
  • Design and implement end-to-end ML pipelines autonomously (data→model→deployment→monitoring).
  • Contribute to APIs, tools, and libraries used by AI team members daily.

Skills

Python
APIs
Kubernetes
Docker
Cloud
Mentor

Tools

APIs
Kubernetes
Docker
Cloud

Job description

Aily Labs in Madrid is hiring a MID AI/ML Engineer to build and scale AI/ML infrastructure powering our decision intelligence platform. You will implement end-to-end ML pipelines, optimize deployments, and collaborate with data scientists and software engineers to ship reliable systems.

The role emphasizes production-ready models, robust APIs, and cloud-based scaling, with a hybrid work policy (2 days in the office).

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