Senior AI Architect – AI Engineering
3 weeks ago
Our values
reflect the culture that the Group’s teams around the world live and express each day. The strength of AXA’s company culture and its outstanding managerial continuity over more than 40 years can also be seen in the proximity of its values across the various periods.
Courage, Integrity, One AXA and Customer First
are the four core values adopted by the Group since 2016.
Our Vision
is to transform AXA’s value proposition
“from payer to partner” , by delivering new services complementing the traditional insurance coverage and by building new business models to increase the protection of our customers.
Join us as a Senior AI Architect within AI Engineering Division of DAAS (Data, AI & Analytics Services), and lead the design and implementation of cutting-edge artificial intelligence solutions for the insurance industry. You'll collaborate with cross-functional teams to understand business needs and architect end-to-end AI systems, leveraging state-of-the-art machine learning models and technologies. If you're passionate about shaping the future of AI in insurance and driving innovation, this role offers an exciting opportunity to make a significant impact.
Technical skills:
Expertise is required in the following fields:
in designing and implementing end-to-end AI architecture, integrating state-of-the-art models such as BERT, GPT, and XLNet for natural language processing (NLP), as well as ResNet, VGG, and EfficientNet for computer vision tasks.in Generative AI tech – LLMs, LLM Ops, RAG, Prompt Engineering, LLM Models fine tuningin deploying and managing AI solutions on cloud platforms such as AWS, Azure, or Google Cloud, leveraging services like AWS SageMaker, Azure Machine Learning.understanding of machine learning algorithms and techniques, including large and small language models, convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformer models, and attention mechanisms.experience in building and optimizing AI pipelines at scale, utilizing frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and SpaCy for efficient model training and deployment.with software engineering best practices and tools tailored for AI development, including version control systems (e.g., Git), CI/CD pipelines (e.g., Jenkins, GitLab CI), containerization (e.g., Docker), and orchestration (e.g., Kubernetes).
Soft skills:
communication skills to facilitate collaboration between business stakeholders and technical teamsin managing large AI teams of more than 10-15 membersresults-orientation and effective time management skills A collaborative team player comfortable working within a global team environmentto quickly establish relationships with stakeholders to collaborate on AI use casescuriosity, and innovation capability to drive AI initiatives forwardworking within a multidisciplinary team in a fast-paced environment
Background and experience:
Bachelor’s/Master's Degree in a quantitative field At least 13+ years of experience in ML&AI-related fields, with a strong emphasis on AI architecture and model development.
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