MLOps Engineer

Emploi pas sur LinkedIn

🕒 il y a 10 jours

🇩🇪 Allemagne – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🤖 Ingénieur Machine Learning

🗣️🇺🇸🇬🇧 Anglais requis

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Logo of SHOP APOTHEKE EUROPE

SHOP APOTHEKE EUROPE

1001 - 5000 employés

🏥 Santé

⚕️ Assurance santé

🛒 Commerce de détail

Healthcare • Healthcare Insurance • Retail

SHOP APOTHEKE EUROPE est une société pharmaceutique axée sur la fourniture de services de santé et pharmaceutiques en Europe. Opérant sous le nom commercial Redcare, elle met l'accent sur une approche axée sur les personnes en pharmacie, visant à accompagner les individus tout au long de leur parcours de santé. L'entreprise s'engage pour la durabilité, alignant ses stratégies avec l'Accord de Paris sur le climat pour contribuer positivement à la santé environnementale. SHOP APOTHEKE EUROPE s'engage également dans les affaires publiques, les relations avec les investisseurs, et offre des opportunités de carrière à ceux qui souhaitent rejoindre leur équipe animée par une mission.

Description

• Build, operate, and improve ML/AI solutions in production • Collaborate with data scientists and engineers in cross-functional product teams • Contribute to continuous improvement of MLOps practices and platform • Build and operate containerized services using orchestration platforms such as Kubernetes • Troubleshoot production issues and improve reliability, performance, and cost-efficiency of ML/AI services • Develop maintainable and well-tested Python code for production services, automation, and internal tooling • Build and improve CI/CD pipelines for ML/AI services • Implement data and model versioning, validation, and observability throughout the ML lifecycle • Contribute to technical designs and architecture decisions • Participate in code reviews • Integrate automated security checks into delivery pipelines and follow secure development and operations practices

🎯 Exigences

• Practical experience in MLOps, DevOps, platform engineering, or software engineering, including deploying and operating ML/AI solutions in production • Solid software engineering skills in Python, including automated testing, version control, and code review • Hands-on experience with Docker and container orchestration platforms such as Kubernetes • Experience with CI/CD tools such as GitHub Actions or Jenkins • Familiarity with ML lifecycle practices such as model packaging, versioning, validation, deployment, and monitoring • Experience with tools such as MLflow or Kubeflow is welcome • Solid understanding of software architecture and secure software development and delivery practices

🏖️ Avantages

• Flexible work location when the job does not require office presence, including up to 20 days per year from anywhere within the EU • Creative team events and regular success celebrations • Anonymous, free professional psychological support via nilo • Internal and external training opportunities and professional development support • Fully funded Deutschlandticket • Urban Sports Club M membership

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