MACHINE LEARNING ENGINEER F/H

2 days ago


Iowa LA United States Selfing France Full time

Secteur d'activité : Distribution / Retail

Localisation :

Type d'offre : Indépendants/freelances

SELFING est une société de conseil active dans les métiers de l'ingénierie, de la technologie de l'information, des services opérationnels et fonctionnels des entreprises.

L'ADN de SELFING se résume en 5 fortes valeurs : professionnalisme, expertise, fiabilité, qualité, réactivité.

Vous intégrerez notre département Digital Data et travaillerez sur notre plateforme digitale, la Product Digital Platform (PDP) . Cette plateforme offre des solutions numériques basées sur les données pour créer des offres d'amélioration de l'habitat.

En tant que membre de l'équipe Data de la plateforme, vous serez impliqué dans des initiatives liées à l'intelligence artificielle (IA). Vos principales responsabilités incluront :

  1. Industrialiser les solutions IA développées en R&D.
  2. Construire et maintenir la plateforme de machine learning (ML).
  3. Assurer le fonctionnement des solutions ML.
  4. Collaborer avec les Data Scientists et l'équipe Digital.

Un Machine Learning (ML) Engineer est un spécialiste en informatique axé sur la recherche, la conception et la construction de systèmes d'intelligence artificielle (IA) autonomes. L'ingénieur en apprentissage automatique sera responsable de :

  1. Collaborer étroitement avec les data scientists pour identifier les opportunités d'impact business.
  2. Contribuer à la production et à l'industrialisation de systèmes d'apprentissage automatique innovants.
  3. Créer des systèmes intelligents pour la surveillance des modèles de ML.
  4. Partager les bonnes pratiques sur les outils de ML.
  5. Coacher, mentorer et recruter de nouveaux membres.

Compétences requises :

  1. Solides compétences en ingénierie logicielle.
  2. Capacité à écrire un code de qualité pour la production.
  3. Aptitude à choisir les méthodes de ML appropriées.
  4. Expérience dans la mise en production de solutions de ML.
  5. Compréhension du cycle de vie de l'ingénierie du ML.

Stack demandée : Python, SQL, Spark, Docker/Kubernetes, GIT, VertexAI, GCP, ZenML, DEVOPS.

Vous vous reconnaissez dans notre projet et nos valeurs ? REJOIGNEZ-NOUS

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