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Senior Machine Learning Operations Engineer

Senior Machine Learning Operations Engineer

Intellias, , Spain, España
Hace 26 días
Descripción del trabajo

Senior Machine Learning Operations Engineer

Overview

Join a transformative data and AI platform initiative aimed at modernizing enterprise-scale capabilities and enabling real-time decision-making. This project delivers a comprehensive roadmap covering AI, MLOps, data governance, and platform scalability, supporting a shift towards data-first operations and intelligent automation.

What you will do

  • Design and implement Machine Learning infrastructure within AWS Sagemaker for scalable, secure, and automated model training, deployment, and monitoring pipelines.
  • Set up and maintain MLFlow for model tracking, experiment management, and governance with a focus on production-readiness and reproducibility.
  • Integrate data sources and pipeline orchestration using Apache Airflow to feed data into SageMaker model training workflows.
  • Build CI / CD pipelines for robust testing, linting, vulnerability scanning, and seamless model deployment.
  • Automate and manage infrastructure provisioning using Terraform , ensuring repeatable and compliant infrastructure-as-code practices.
  • Implement monitoring and observability, enabling fine-grained insights into pipeline performance, resource usage, and anomaly detection.
  • Collaborate closely with Data Scientists to streamline experimentation workflows, optimize pipeline runtimes, and scale computational resources.

What you need for this

  • 4+ years of experience in DevOps or MLOps roles with a strong focus on ML model lifecycle automation and infrastructure scalability.
  • Proficiency with AWS SageMaker and associated AWS services such as S3, IAM, Secrets Manager, and CloudWatch.
  • Practical experience with ML pipeline tooling such as MLFlow for model tracking and Apache Airflow for workflow orchestration.
  • Solid skills in scripting and automation using Python, Bash, and YAML.
  • Experience building and maintaining CI / CD workflows.
  • Familiarity with Infrastructure as Code principles and hands-on experience with Terraform .
  • Comfortable working in cross-functional teams with Data Scientists, helping bridge experimentation and production environments.

    • Will be a plus

  • Experience with data lake formats for managing large-scale tabular data in ML workflows.
  • Knowledge of advanced resource optimization and auto-scaling strategies.
  • Prior work in highly regulated domains such as identity verification, where traceability, explainability, and compliance are critical.
  • Understanding of GenAI / LLM workflows and how to enable scalable infrastructure to support those pipelines.
  • Familiarity with FastAPI for building RESTful ML service interfaces.

    • Seniority level

  • Mid-Senior level

    • Employment type

  • Full-time

    • Job function

  • Industries

    • Referrals increase your chances of interviewing at Intellias by 2x

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    Machine Learning Engineer • , , Spain, España