Padmi
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Alinia

AI compliance · LLM guardrails

Machine Learning Engineer

Barcelona · HybridPosted 7 days ago
Machine learningMid-levelFull Time
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Machine Learning Engineer

Barcelona

Research & Engineering

Hybrid

Full-time

About the Role

As Alinia’s Machine Learning Engineer, you will be responsible for building and scaling the ML infrastructure that powers our AI guardrails, evaluation pipelines, and enterprise-grade deployments. You’ll work at the intersection of cutting-edge ML research and production, ensuring that our models and detectors move seamlessly from prototype to reliable, performant, and secure systems used in real-world regulated environments.

This is a hands-on, high-impact role where you will own the full lifecycle of ML engineering: from infrastructure design, deployment pipelines, and monitoring, to optimization and productionization of research outputs.

Responsibilities

  • Build and maintain robust ML infra (training, serving, monitoring).
  • Deploy LLMs, RAG pipelines, and detectors into production at scale.
  • Translate research prototypes into production-ready APIs/services.
  • Manage CI/CD pipelines, observability, experiment tracking.
  • Optimize for latency, cost, and reliability.
  • Ensure security, compliance, and privacy in enterprise environments.
  • Collaborate closely with ML researchers, back-end engineers, and product teams.

Requirements

  • 4+ years as ML Engineer / MLOps / related role.
  • Strong Python + ML frameworks (PyTorch/TensorFlow).
  • Cloud platforms (AWS/GCP/Azure) + Kubernetes/Docker.
  • Track record deploying ML models in production (REST/gRPC, FastAPI).
  • CI/CD pipelines, monitoring, experiment tracking (MLflow, W&B).
  • Understanding of enterprise security & compliance (SOC2, ISO 42001, EU AI Act).

Nice to have

  • LLMs, RAG systems, or retrieval optimization.
  • Experience with GPUs/distributed training.
  • Work in regulated industries (finance, insurance, healthcare).
  • Contributions to open-source ML tooling.

Why Join Alinia?

  • Build AI safety infrastructure at the frontier of enterprise adoption.
  • Work on applied ML with real-world impact.
  • Competitive compensation + meaningful equity.
  • Early, high-impact role in a mission-driven startup.

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Req ID: R1

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