Top Artificial Intelligence Jobs in Paris

Lead AI-enabled financial planning and strategic analysis, build data-backed business cases, refine unit economics, deliver executive-level insights, integrate ML into FP&A, and track KPIs to drive profitability and strategic decisions.

Design, implement, and optimize AI-driven solutions across the claims lifecycle (intake, investigation, adjudication). Build ML models for data extraction, fraud detection, reserve setting, subrogation, and adjudication decision engines. Collaborate with underwriting, fraud, legal, and IT to integrate models into operations and improve efficiency, accuracy, and compliance.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Lead budgeting, forecasting, and variance analysis while building AI-driven financial models, scenario planning, KPIs, and dashboards. Automate FP&A processes, deliver insights to senior leaders, and collaborate with cross-functional teams to improve forecast accuracy and strategic decision-making.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Lead integration of AI-driven tools into tax provision, planning, and multi-jurisdictional compliance. Design ML/analytics solutions for sales and payroll tax, enhance regulatory filings, support audits, and collaborate with finance, legal, and technology teams. Monitor tax regulation changes, document AI tax models for transparency and governance, and continuously refine models for scalability, reliability, and compliance.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Lead modernization of month-end and year-end close processes using AI and automation. Prepare, review, and validate journal entries, accruals, and financial statements. Implement anomaly detection, automated reconciliations, variance analysis, and predictive insights. Collaborate with data teams to structure finance data for ML use cases and design audit-ready, scalable reporting workflows.

Manage and optimize end-to-end account reconciliations, intercompany eliminations, and chart-of-accounts governance. Identify discrepancies, perform variance analysis, and implement AI-driven automation and anomaly detection to reduce manual effort and accelerate close. Collaborate with cross-functional teams to resolve mismatches and improve financial data quality and reporting accuracy.

Build and maintain operating and cash-flow models, apply AI/ML and data techniques to automate forecasts, run sensitivity and scenario analysis, translate strategy into financial outcomes, support fundraising/M&A/pricing, and create dashboards and reports for stakeholders.

Lead enterprise AI strategy, operating model, governance, platform enablement, and CoE to deploy safe, compliant, and scalable AI across R&D, Clinical, Manufacturing, Quality, Commercial, and Corporate functions in a regulated pharmaceutical environment.

As a Customer Support Expert, you will provide customer support via social media and email, representing brands and resolving requests professionally.

The AI Engineering Manager will build and lead a high-performing team focused on AI agents, workflow orchestration, and navigating evolving technology, ensuring clarity and delivering impactful results.

The Manager of Molecular Generation Team leads a multidisciplinary group in developing methods for designing novel molecules using AI and physics-based techniques. Responsibilities include strategic leadership, team management, and facilitating collaboration for effective molecular generation workflows.

The role involves leading design for AI-native products at Synthesia, focusing on improving interaction patterns and enhancing user experience in AI-driven workflows.

Develop and refine NLP projects by improving LLM models, implementing production models, and conducting performance experiments.

The AI Solutions Manager drives strategy and commercialization of AI solutions, focusing on scalable solutions, partnerships, and sales enablement.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

As a Deployed AI Engineer, you'll integrate software into systems, collaborate on customer requirements, and troubleshoot issues while showcasing AI capabilities.

Lead the AIVM product development, overseeing architecture, strategy, and execution while collaborating across teams for successful platform launch.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.