This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
This is a Unified Application for our AI-First IT Transformation portfolio. We recognize that top-tier AI talent often has skills that span multiple domains. By applying here, your profile is evaluated by our core IT strategy team for multiple high-impact leadership and technical roles powering the entire enterprise, ensuring we find the right home for your specific expertise.
Job Responsibility:
Lead the hands-on development of core Enterprise IT Business software leveraging AI components and LLM infrastructure with both traditional and Generative AI model deployment
Build and industrialize agentic AI systems and multi-agent frameworks, ensuring secure and effective use of GenAI technologies at the platform level
Design and implement robust foundational data pipelines, perform advanced statistical analysis, and develop new ML models to drive autonomous system behavior
Design large-scale, distributed AI/ML systems optimized for low latency, high throughput, and developer-friendliness (Inference optimization)
Establish evaluation frameworks to measure AI quality (accuracy, hallucination rates) and overall system reliability across the Enterprise AI Factory
Requirements:
3-5+ years of experience in Software Engineering, Data Science, or Machine Learning (Staff level)
6-8+ years (Senior Staff)
8-12+ years (Principal level)
Expert-level server-side development (Python, Java, Go) OR deep expertise in statistical modeling, ML algorithms, and LLM fine-tuning
Direct experience with RAG architectures, LLM APIs, and Vector Databases (e.g., Pinecone, Milvus)
Hands-on experience with Kubernetes, CI/CD, and distributed systems for large-scale AI deployment
Nice to have:
Experience with multi-turn dialogue management, Text-to-SQL systems, and causal inference
Understanding of adversarial defense and security principles as they apply to AI model integrity
PhD or Master’s in Computer Science, Applied Mathematics, or Machine Learning