Consultant Lead Maching Learning Engineer (H/F)

JR France; Paris; Sur place; EUR 60 000 - 90 000; Plein temps

Résumé du poste

Une entreprise dynamique recherche un Consultant Lead Machine Learning Engineer pour diriger le déploiement et l'intégration de solutions ML. Le candidat idéal a une solide expérience en ingénierie des opérations ML, avec des compétences techniques avancées en Python et en DevOps. Vous travaillerez en étroite collaboration avec des équipes de données et de produits pour assurer le succès des solutions ML, tout en proposant des améliorations continues pour optimiser les infrastructures existantes.

Qualifications

• 5 ans d'expérience significative en ingénierie des opérations ML.
• Compétences en Python, PySpark et technologies DevOps.
• Capacité à résoudre des problèmes complexes en environnement ML.

Responsabilités

• Orchestrer le déploiement continu et l'intégration de modèles ML.
• Collaborer avec des équipes interfonctionnelles pour intégrer des solutions ML.
• Proposer et mettre en œuvre des améliorations pour optimiser la fiabilité des systèmes.

Connaissances

Python

PySpark

Docker

Kubernetes

CI/CD

Machine Learning Algorithms

Cloud Platforms

Git

Formation

Master’s or Ph.D. in Computer Science, Data Science, or related field

Description du poste

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Consultant Lead Machine Learning Engineer (H/F), Paris

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Client:

SOFTEAM

Location:

Paris, France

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

538976890372541644832761

Job Views:

2

Posted:

25.05.2025

Expiry Date:

09.07.2025

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Job Description:

Key Responsibilities:

• Model Deployment: Orchestrate continuous deployment and integration of machine learning models, ensuring optimal functionality across various environments.
• Scalability: Develop and implement infrastructures to support scaling ML solutions across different countries while respecting local specifications.
• Monitoring and Maintenance: Implement robust monitoring systems to track performance, identify anomalies, and continuously optimize models.
• Infrastructure and Automation: Design and manage automation pipelines for efficient handling of deployments and updates of machine learning models.
• Cross-Functional Collaboration: Collaborate with data scientists, software engineers, and product teams to ensure smooth and successful ML solutions integration.
• Continuous Improvement and Innovation: Analyze performance feedback and actively propose and implement improvements to optimize system reliability and ML model efficiency.
• Autonomy and Leadership: Operate with a high degree of autonomy in decision-making and demonstrate leadership in proposing new strategies and solutions for enhancing ML infrastructure.

Qualifications:

• Education: Degree in Computer Science, Data Science, or related field (Master’s or Ph.D. preferred).
• Experience: 5 years of significant experience in machine learning operations engineering with demonstrable success in deploying and managing ML models in production.
• Technical Skills: Proficiency in Python and PySpark, DevOps technologies like Docker, Kubernetes, CI/CD, and machine learning algorithms and best practices. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud. Proficiency in Git and experience in agile development methods.
• Problem-Solving and Proposal Skills: Ability to diagnose and resolve complex issues in ML production environments and propose innovative solutions.
• Communication and Initiative: Effective communication skills for conveying complex concepts and a proactive approach in taking initiative and driving projects forward.