Ingénieur d'application principal (Lead Application Engineer) – Solutions de gestion de la performance des actifs (APM) H/F/Lead Application Engineer – Asset Performance Management Solutions H/F

GE Vernova

Massy, France

Full Time

Posted August 4, 2026

Power Generation

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Listing evidence and provenance

Source: workday View original listing
Freshness: Open in the current public read path; this is not an employer guarantee.Last observed October 4, 2026
Classification: Modern power-system classification not yet published for this listing.Legacy source industry field: Power Generation
Pay provenance: Pay not available

Job Description

Rejoignez l'équipe R&D de GE Vernova en tant que pont technique entre la gestion de produit et le développement de produits.

Key Responsibilities

Traduire les exigences de gestion de produit, les besoins des clients et les tendances du marché en conceptions techniques détaillées, spécifications algorithmiques et documents d'architecture pour les solutions de performance et de fiabilité des actifs.
Développer des prototypes de preuve de concept et des modèles mathématiques utilisant Python, Java et des outils statistiques/d'optimisation pour valider les solutions proposées pour les cas d'utilisation RCM, APM et gestion des actifs.
Concevoir et affiner des algorithmes mathématiques, statistiques et d'optimisation pour la maintenance prédictive, l'analyse des modes de défaillance, l'évaluation de l'état de santé des actifs et l'optimisation des coûts du cycle de vie.
Collaborer avec la gestion de produit pour comprendre les exigences de fonctionnalités et les besoins des clients, et travailler avec les équipes de développement pour garantir la faisabilité technique et le transfert fluide des spécifications et prototypes.
Rédiger des livres blancs techniques, des résumés de solutions et présenter des contenus lors de conférences industrielles pour établir un leadership d'opinion dans la gestion de la performance des actifs et l'ingénierie de la fiabilité.
Influencer l'orientation technique par des recommandations basées sur les données, des analyses concurrentielles et une expertise métier afin d'orienter les décisions de stratégie produit.
Identifier des opportunités d'innovations brevetables dans l'analyse de la performance des actifs, les algorithmes de maintenance prédictive et les techniques d'optimisation pour renforcer le portefeuille de propriété intellectuelle de GE Vernova.
Fournir des conseils techniques et du mentorat aux membres des équipes de développement sur les concepts métiers, les approches algorithmiques et l'architecture des solutions.
Analyser les tendances du marché, les normes industrielles (ISO 55000, CEI, cadres RCM) et les exigences clients pour proposer de nouvelles capacités algorithmiques et des améliorations produits pour les solutions APM de GE Vernova.
Translate product management requirements, customer needs, and market insights into detailed technical solution designs, algorithm specifications, and architecture documents for asset performance and reliability solutions.
Develop proof-of-concept prototypes and mathematical models using Python, Java, and statistical/optimization tools to validate proposed solutions for RCM, APM, and asset management use cases.
Design and refine mathematical, statistical, and optimization algorithms for predictive maintenance, failure mode analysis, asset health scoring, and lifecycle cost optimization.
Work with Product Management to receive and understand prioritized feature requirements and customer needs and collaborate with Development teams to ensure technical feasibility and smooth handoff of solution specifications and prototypes.
Author technical white papers, solution briefs, and present materials at industry conferences to establish thought leadership in asset performance management and reliability engineering.
Influence technical direction through data-driven recommendations, competitive analysis, and domain expertise to inform product strategy decisions made by Product Management.
Identify opportunities for patentable innovations in asset performance analytics, predictive maintenance algorithms, and optimization techniques to strengthen GE Vernova’s Intellectual Property portfolio.
Provide technical guidance and mentoring to development team members on domain concepts, algorithmic approaches, and solution architecture.
Analyse market trends, industry standards (ISO 55000, IEC, RCM frameworks), and customer requirements to propose new algorithmic capabilities and product enhancements for GE Vernova’s Asset Performance Management solutions.

Requirements

Master’s or PhD in Engineering, Applied Mathematics, Statistics, Operations Research, or related quantitative discipline from an accredited institution, or equivalent knowledge or experience.
Minimum 8 years of experience in R&D, algorithm development, or solution engineering roles. Minimum of 3 years working at the intersection of product management and engineering/development teams, translating business requirements into technical specifications.
Extensive domain experience in Reliability Centered Maintenance (RCM), Asset Performance Management (APM), and/or Asset Management within asset-intensive industries (utilities, energy, oil & gas, manufacturing).
Strong proficiency in Python and Java, with hands-on experience developing algorithms, data pipelines, or analytical tools.
Solid foundation in mathematical modeling, statistical analysis, and optimization techniques (e.g., linear/nonlinear programming, Bayesian methods, survival analysis, Monte Carlo simulation).
Proven track record of publishing, presenting at industry forums, and influencing product direction through technical thought leadership.
Familiarity with industry standards relevant to asset management and reliability (ISO 55000/55001, PAS 55, IEC 60300 series, SAE JA1011/JA1012 for RCM).
Knowledge of modern Asset Performance Management platforms, predictive analytics trends, and digital twin / condition-based maintenance developments.
Experience working in agile product development environments, collaborating with product owners and scrum teams.
Exposure to machine learning and data science techniques applied to predictive maintenance, anomaly detection, or asset health analytics.
Demonstrated ability to communicate complex technical concepts to diverse audiences and build strong working relationships across Product Management, Engineering, and Customer-facing teams.
Familiarity with enterprise integration patterns, APIs, and data exchange standards relevant to APM/EAM platforms (e.g., OPC-UA, MQTT, REST/GraphQL).
Experience in transmission and distribution (T&D) systems is preferred.