Seeking a highly motivated Senior Cloud Platform Developer to build automated solutions in the cloud, leveraging AI technologies and traditional development practices focusing on DevOps, IaC, and AI-driven automation.
Responsibilities
Design and implement automated cloud solutions using AWS services, ensuring scalability, resilience, and security.
Create and deploy AI agents to optimise operations, automate decision-making, and improve system responsiveness.
Develop and maintain CI/CD pipelines using tools such as Jenkins, GitLab, and GitHub Actions.
Build and deploy AI-enhanced automation workflows, integrating ML models and intelligent decisioning where applicable.
Automate infrastructure provisioning and configuration using Terraform, CloudFormation, or Ansible.
Requirements
Nice to have: AWS certifications (Solutions Architect, DevOps Engineer)
Support the Channel Planning and Analytics strategic plan which will support better service levels with less inventory and optimized safety stocks
Compensation
The salary range for this role is $63,300 to $83,840 Michigan based applicants.
The salary range for this role is $69,300 to $91,790 Non Bay-Area California based applicants.
Responsibilities
Support the Channel Planning and Analytics strategic plan
Own master data and inventory parameters for Service Center materials
Support development, launch, and continuous improvement of part inventory stocking models and strategies
Evaluate and analyze system outputs to ensure correct materials are being ordered
Coordinate and execute transactional movements of materials to optimize and reduce logistics costs
Requirements
Bachelor's in Data Analytics, Supply Chain, Engineering or related field
Define methodologies aimed at strengthening the safety of components based on artificial intelligence for autonomous and connected vehicles, specifically responding to ISO/PAS 8800 standards in the automotive domain.
Responsibilities
Analyse des Données et ODD : Évaluer la complétude et la représentativité des bases de données d'entraînement et de validation par rapport au domaine de conception opérationnel (ODD) visé pour la détection des feux tricolores et panneaux de signalisation.
Vérification de la Robustesse : Améliorer une chaîne de tests de Vérification et Validation (V&V) pour évaluer la résistance des modèles face aux perturbations (tests en boîte noire et boîte blanche).
Explicabilité (XAI) : Implémenter des méthodes d'explicabilité pour interpréter les décisions de l'algorithme et vérifier qu'il s'appuie sur les caractéristiques pertinentes de l'environnement.
Sécurité Fonctionnelle et Optimisation : Proposer des architectures redondantes et des contrôles de plausibilité pour sécuriser la détection des feux tricolores.
Documentation et Déploiement : Consolider un framework 'Trustworthy AI' et rédiger la documentation technique de référence pour guider les équipes de développement.
Requirements
Bac +5
Ecole d’Ingénieur avec Spécialisation Intelligence Artificielle
Nice to have: Appétence pour la recherche et l’innovation
Responsible for building and deploying machine learning models in production environments, designing and implementing ML pipelines, and providing mentorship.
Responsibilities
Designing and developing machine learning (ML) models and algorithms
Implementing and maintaining ML pipelines and workflows
Collaborating with data scientists and analysts to deploy and monitor ML models
Developing and implementing ML deployment and monitoring strategies
Providing guidance and mentorship to junior ML engineers
Channel Planner - For Future ConsiderationNewRivian Automotive · Irvine, US