Top Remote Jobs in France

Evaluate search engine results and provide feedback on text, audio, images, and videos to improve AI-powered search and recommendation experiences. The role requires online research, critical thinking, relevance assessment, quality control, and adherence to productivity standards. It is flexible, part-time, remote work for candidates residing in France who are proficient in English and French. No prior experience is required, but applicants must complete training and pass a client assessment.

As an Account Manager, you will manage high-value hotel accounts, ensuring client retention, driving revenue, and optimizing software use for success.

Own a portfolio of enterprise accounts, guiding customers from deployment to measurable value across SUSE’s Linux, cloud-native, edge, and AI solutions. Develop customer success plans, drive adoption, retention, renewals, and expansion, build executive relationships, and coordinate Support, Consulting, Engineering, Training, and Sales teams. Translate customer health insights into internal product and go-to-market improvements. The role requires fluent German and English, DACH enterprise experience, commercial judgment, and 5–10% travel.

Provides reception, office administration, mail handling, meeting coordination, supply and vendor management, event organization, travel and expense support, facilities coordination, onboarding assistance, and confidential document handling. The role is fully office-based, Monday through Friday, and requires strong organization, communication, customer service, and Microsoft Office skills, along with English and Polish proficiency at B2 level.

Leads business operations for a remote technology company, focusing on KPI performance, bottleneck resolution, scalable workflows, operating cadences, systems design, cross-functional initiatives, and executive support. Manages operational contributors, drives strategic projects from inception through handoff, improves collaboration across departments, and establishes high execution standards. The role combines hands-on operational execution, team leadership, data-informed decision-making, and organization-wide process improvement.

Analyze direct marketing campaign results, support sales and marketing teams with data-driven recommendations, conduct statistical studies involving segmentation and scoring, and develop automation projects and Power BI dashboards. The role requires working with high-volume databases, SQL, Python, cloud platforms, and AI/ML techniques while communicating findings to French, Italian, and English-speaking stakeholders.

Design and deploy AI microservices and LLM-powered applications using Python, REST/gRPC, Docker, and Kubernetes. Build RAG, hybrid search, agent, fine-tuning, quantization, evaluation, and prompt-guardrail systems. Monitor model quality, latency, cost, and security while integrating databases and SIEM/SOC platforms. Establish MLOps, testing, observability, and compliance standards for high-security public-safety environments. Collaborate with security teams on CJIS and FedRAMP audits, with optional travel to Japan and the United States.

Manage end-to-end data engineering, cloud, and machine learning consulting projects for EMEA customers. Responsibilities include defining scope, objectives, budgets, timelines, and resources; coordinating cross-functional teams and stakeholders; managing risks, escalations, and customer communications; improving delivery processes; and ensuring adherence to project management standards and methodologies.

Lead and mentor a globally distributed engineering team while contributing to coding, architecture, peer reviews, and technical decisions. Design and deliver scalable user-facing systems, promote CI/CD, testing, code quality, and DevOps practices, and improve engineering workflows. Collaborate with product, design, data, and AI specialists to shape roadmaps and integrate personalized learning capabilities. Manage engineers through regular one-to-ones, feedback, and career support.

Build Python-based backend services, APIs, and integrations that embed AI capabilities into a SaaS platform. Develop scalable customer-facing features, connect AI outputs to workflows and dashboards, collaborate with product, design, and platform teams, and implement observability, monitoring, and error handling. Contribute to the AI integration stack, including SDKs, MCP servers, and LLM orchestration.