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# Machine Learning Engineer Expert

- **Company:** AXA
- **Location:** Paris, France
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Testing, Python (Programming Language), Machine Learning, Routing, Regression Testing, Software Engineering, Retrieval-Augmented Generation, Prompt Engineering, Model Validation, Caching, Generative AI, Agentic-AI, AI Platforms, Low Latency, Machine Learning Operations
- **Published:** October 10, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=90bd6be923037fb4

## About the Role

5+ years delivering AI/ML-enabled products, GenAI applications, or AI platforms in production environments, with experience across the full lifecycle from design and implementation to monitoring and continuous improvement.

 * Experience contributing to evaluation, observability, reliability, or optimisation practices for GenAI applications such as RAG, conversational assistants, workflow automation, or agentic systems.
 * Good understanding of AI operational drivers, including quality, latency, cost, usage, safety, privacy, and business value, with the ability to balance them pragmatically.
 * Demonstrated leadership experience in managing engineering teams or cross-functional project teams.
 * Experience working in the insurance, financial services, or another regulated industry is a plus.

Technical skills

 * Strong software engineering foundations for production-grade AI systems, including Python or similar languages, APIs, integration patterns, monitoring, and automation.
 * Solid understanding of GenAI application patterns, including RAG, conversational assistants, workflow automation, and agentic or tool-using systems.
 * Ability to define and operate evaluation approaches for GenAI systems, covering quality criteria, regression testing, human feedback, performance measurement, reliability, and risk controls.
 * Understanding AI consumption and cost drivers, such as model selection, context management, prompt design, caching, routing, orchestration, infrastructure choices, and usage governance.
 * Experience with observability and operational monitoring for AI applications, including tracing, latency, reliability, usage, cost efficiency, and continuous improvement indicators.
 * Ability to establish practical guardrails for responsible AI engineering, balancing performance, cost, safety, security, privacy, sustainability, and compliance requirements.

Soft skills / transversal skills

 * Team management: experience in leading, coaching junior team members
 * Project management: lead end-to-end GenAI initiatives, define scope, milestones, timelines, budgets, resource planning, risk management, and ensure on-time, on-budget delivery.
 * Stakeholder management: partner with product, business units, compliance, security, legal, and operations; translate business needs into concrete requirements; manage expectations; maintain governance artifacts and transparent status updates.
 * Storytelling and communication: craft compelling narratives around GenAI initiatives, translate complex concepts into clear executive summaries and user stories, and present results effectively to technical and non-technical audiences; develop metrics dashboards and impact narratives.
 * Agile mindset with a commitment to continuous improvement, iterative delivery, backlog prioritization, and value-driven outcomes.
 * Collaboration and adaptability: strong teamwork across cross-functional and multicultural environments; excellent English communication and interpersonal skills.
 * Passion for solving challenging problems with cutting-edge GenAI technologies, coupled with curiosity and a proven ability to learn and apply new techniques and research advances.

## Description

* Engage proactively with AXA entities and business units, facilitating ongoing dialogue, co-constructing AI solutions, and guiding stakeholders through complex decisions to ensure alignment, adoption, and shared success.
 * Lead the design, development, deployment, and operation of AI and GenAI solutions that deliver measurable value for AXA entities.
 * Contribute to the evolution of shared AI engineering practices, including evaluation, observability, performance, cost efficiency, safety, and lifecycle governance.
 * Support key topics such as GenAI application evaluation and AI consumption optimisation, while maintaining flexibility to take ownership of new AI engineering priorities over time.
 * Collaborate with cross-functional teams including data scientists, data engineers, product managers, platform teams, and business stakeholders to identify opportunities and translate them into robust technical solutions.
 * Define reusable patterns, standards, and guardrails for scalable, reliable, secure, and responsible AI systems across the organisation.
 * Lead and mentor AI engineers, fostering engineering excellence, pragmatism, curiosity, and continuous improvement.