Head of AI
Paris
â ď¸ We'll shut down after Aug 1st - try foođŚ for all jobs in tech â ď¸
Xpress Automation
esma certified 5-stars vehicle workshop roadside assistance Wheel REPAIR Body and paint repair mechanical servicing smart repair restorations GET A QUOTE RELIABLE AND DEPENDABLE.what sets us apart? Technology Our bodyshop management systems...Key Responsibilities
- Define and execute the companyâs AI strategy aligned with business and product objectivesÂ
- Identify and prioritize high-impact AI/ML use cases across underwriting, pricing, claims, fraud detection, and customer serviceÂ
- Lead the design, development, and deployment of machine learning models across domains such as:Â
- Natural Language Processing (e.g., document parsing, claims narratives, chatbot intent detection)Â
- Computer Vision (e.g., damage assessment from images, document classification, identity verification)Â
- Predictive Modeling (e.g., risk scoring, fraud detection, churn prediction)Â
- Generative AI (e.g., summarization, auto-responses, document synthesis)Â
- AI Agents (e.g., multi-step task automation, dynamic customer support agents, claims triaging assistants)Â
- Collaborate with Product Managers to scope and deliver AI-powered features, ensuring feasibility, performance, and alignment with user needsÂ
- Translate business requirements into robust AI/ML solutions and product-integrated systemsÂ
- Drive the productization of ML models, including testing, deployment, performance monitoring, and continuous iterationÂ
- Design and oversee AI features that are interpretable, user-centric, and embedded in customer-facing workflowsÂ
- Build and lead a high-performing AI/ML team; hire, mentor, and foster a culture of innovation and excellenceÂ
- Partner cross-functionally with Engineering, Product, Design, Actuarial, and Claims teams to integrate AI deeply into the platformÂ
- Establish best practices for model governance, fairness, explainability, and risk controlsÂ
- Define and implement scalable, cloud-based MLOps infrastructure for training, deployment, and monitoringÂ
- Define and implement scalable, cloud-based MLOps infrastructure for training, deployment, and monitoring
- Own data strategy, including acquisition, labeling, enrichment, and privacy-compliant usage of structured, unstructured, and image data
- Collaborate with data engineering to ensure high-quality, scalable pipelines across structured and visual inputs
- Stay up to date with the latest advancements in computer vision, NLP, LLMs, AI agents, and foundational model ecosystems
- Evaluate and integrate third-party CV/AI APIs, pretrained models, and partnerships as needed to accelerate innovation
Qualifications
- 10+ years in AI/ML roles, with at least 5+ years in leadership roles.
- Proven experience applying AI/ML in insurance, fintech, or other regulated industries
- Strong knowledge of machine learning, deep learning, NLP, computer vision, and applied statistics
- Hands-on experience deploying CV models in production for tasks such as image classification or object detection
- Experience leading cross-functional product development of AI features and tools
- Proficient in Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, OpenCV)
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (e.g., MLflow, Kubeflow, Airflow)
- Strong communication and storytelling skills with both technical and non-technical stakeholders
Nice-to-Haves
- Background in insurance claims automation, computer vision pipelines, or document AI
- Familiarity with LLMs, prompt tuning, and GenAI techniques
- Experience designing and deploying AI agents for process automation or customer engagement
- Experience with document understanding pipelines (multi-modal vision + NLP models)
- Masterâs or PhD in Computer Science, Machine Learning, or a related field
- Published work, open-source contributions, or patents in AI/ML or computer vision
Why Join Us?
- We're not just deploying AIâwe're building a platform where AI is the core product. This is your chance to shape a category-defining company, build high-impact systems, and lead innovation from the ground up.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index đ°
Tags: Airflow AI strategy APIs AWS Azure Chatbots Classification Computer Science Computer Vision Data strategy Deep Learning Engineering FinTech GCP Generative AI Kubeflow LLMs Machine Learning MLFlow ML models MLOps Model deployment NLP OpenCV Open Source PhD Pipelines Predictive modeling Privacy Python PyTorch Scikit-learn SQL Statistics TensorFlow Testing
Perks/benefits: Career development
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