Senior AI Engineer – Workday Products

🕒 il y a 1 mois

🌐 Royaume-Uni, Pologne – Distant

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⏰ Temps Plein

🟠 Senior

🤖 Ingénieur IA

🇬🇧 Parrain de Visa de Travailleur Qualifié UK

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👻 Score fantôme 32%

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🗣️🇺🇸🇬🇧 Anglais requis

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Logo of Kainos

Kainos

1001 - 5000 employés

🏥 Santé

📣 Marketing

📦 Logistique

💰 Venture Round en 1986-04

Healthcare • Marketing • Logistics

Chez Kainos, nous utilisons la technologie pour résoudre des problèmes réels pour nos clients, surmonter de grands défis pour les entreprises et simplifier la vie des gens.\n\nNous établissons des relations solides avec nos clients et faisons plus que ce qui est attendu pour transformer leur manière de travailler aujourd'hui et l'impact qu'ils auront demain.\n\nNos deux domaines d'activité spécialisés, les Services Numériques et la Pratique Workday, œuvrent globalement pour des clients des secteurs de la santé, du commerce et du secteur public afin d'améliorer un peu le monde, jour après jour.

Description

• Bridge the gap between data science and software engineering to productionize AI and machine learning solutions. • Work closely with data scientists, software engineers, and product teams. • Deliver robust, scalable AI solutions that enhance Workday Products offerings. • Integrate AI models into production systems. • Optimize performance and maintain the reliability of AI-driven features. • Contribute to the technical growth of the team.

🎯 Exigences

• Solid experience in software development, with proficiency in languages such as Python, Java, or C++, writing clean, efficient, and maintainable code for production grade AI solutions. • Hands-on experience deploying AI/ML models to production environments. • Good understanding of MLOps practices including CI/CD pipelines, model versioning, and monitoring. • Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native AI tools such as SageMaker, Vertex AI, or Azure ML Studio. • Working knowledge of containerization technologies such as Docker and orchestration tools such as Kubernetes. • Skills in data engineering, including building data pipelines, data wrangling, and integrating AI solutions with enterprise data systems. • Exposure to agile software development practices and experience working in agile teams. • Ability to collaborate with cross-functional teams, translate technical requirements into actionable solutions, and communicate effectively with technical and non-technical stakeholders.

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