Lead – AI Acceleration – MLOps / AI Engineer / Data Scientist, GCP, VertexAI, Watsonx, Agentic AI

Overview

Découvrez votre prochaine opportunité au sein d'une organisation qui compte parmi les 500 plus importantes entreprises mondiales. Envisagez des opportunités innovantes, découvrez notre culture enrichissante et travaillez avec des équipes talentueuses qui vous poussent à vous développer chaque jour. Nous savons ce qu’il faut faire pour diriger UPS vers l'avenir : des personnes passionnées dotées d’une combinaison unique de compétences. Si vous avez les qualités, de la motivation, de l'autonomie ou le leadership pour diriger des équipes, il existe des postes adaptés à vos aspirations et à vos compétences d'aujourd'hui et de demain.

Job Summary

Fiche de poste :

We’re seeking a hands-on AI Acceleration Team Lead to drive end-to-end delivery of ML and GenAI solutions—from scoping and prototyping to production, monitoring, and continuous improvement. The ideal candidate brings depth in one core area (Data Science, MLOps, or GenAI Engineering) and breadth across ML fundamentals, GenAI (RAG/agents), and delivery practices. You’ll lead a high impact, cross-functional pod and build on our stack: GCP, Vertex AI, IBM watsonx, and other agent orchestration frameworks (e.g., LangChain/LangGraph)

Key Responsibilities

• End-to-End Solution Leadership: Own the full AI lifecycle: from requirement negotiation with stakeholders to technical architecture, deployment, and post-production monitoring.
• GenAI & Agentic Orchestration: Design and scale sophisticated LLM applications using LangChain and LangGraph. Build multi-agent systems capable of reasoning, tool-use, and workflow automation/decision support for logistics use cases.
• Hybrid Platform Oversight: Serve as the technical lead for our AI stack, optimizing Google Cloud Vertex AI for model training/serving and IBM Watsonx for enterprise-grade governance and scaling.
• Production-Grade MLOps: Ensure the team builds robust CI/CD/CT (Continuous Training) pipelines. Oversee the integration of IaC, vector databases, feature stores, and automated evaluation frameworks.
• Responsible AI & Governance: Implement model monitoring for drift, bias, and "hallucinations" (for GenAI) using watsonx.governance, ensuring compliance with enterprise standards.
• People & Project Leadership: Translate business goals into measurable AI outcomes; manage backlog, risks, timelines, and documentation. Mentor a cross-functional team of AI Engineers and Data Scientists. Act as the "Player-Coach" who can perform deep code reviews while managing project milestones and executive expectations.
  
  

• 4+ years relevant in Data Science, MLE/MLOps, or GenAI Engineering; 1+ end-to-end project led to production (ownership of design→deploy→monitor).
• Depth in one track, plus working breadth across:
• ML/DS: problem framing, feature engineering, model selection, evaluation.
• GenAI: prompt engineering, RAG, agentic patterns, tool use.
• MLOps: CI/CD for ML, observability, rollback, cost/perf tuning.
• Stack: GCP/Vertex AI, IBM watsonx, Python, LangChain/LangGraph (or equivalent orchestration), Git, Docker/Kubernetes, SQL.
• Proven ability to lead cross-functional contributors and deliver measurable business impact.
  

• Experience with Vertex AI (Pipelines, Workbench, Endpoints, Model/Feature Registry) and watsonx.ai / watsonx.governance.
• Familiarity with vector databases and retrieval and RAG evaluation.
• Exposure to MLflow/Kubeflow/Airflow, Terraform/Helm, and LLMs (Gemini, Llama, MistralAI).
• Knowledge of responsible AI controls (evals, guardrails, red teaming) and basic compliance frameworks.
• Experience with production monitoring/incident response for ML/GenAI services (SLAs, on-call, postmortems).
  
  

Education

Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field

Type De Contrat

en CDI

Chez UPS, égalité des chances, traitement équitable et environnement de travail inclusif sont des valeurs clefs auxquelles nous sommes attachés.