Dailymotion

Backend Engineer

• Design and build geo-distributed Backend systems using microservices architecture
• Design and build API-centric systems using REST, GraphQL, and OpenAPI standards
• Design and build distributed authentication and authorization systems
• Design and build queueing and event-driven systems
• Participate in legacy system modernization and incremental migration strategies
• Collaborate on Partner API design with backward compatibility requirements
• Proactivity on evolutions and improvements

Senior Back-End Engineer, Python - API

Frontend Engineer

• Contribute to the team effort to develop new features, fix bugs and deliver a state of the art user experience to a variety of browsers and devices (mobiles, tablets, desktops)
• Maintain existing codebase, with a focus on the HTML video player, and contribute to keep it up to date with current technology and best practices (tests, coding guidelines, continuous deployment)
• Write and maintain technical specifications and technical documentation about the codebase
• Take part in a collaborative culture that encourages every member of our team to bring their added value
• Mentor junior engineers and contribute to growth of the team

Senior Frontend Engineer – Backbone Player

Full-stack Engineer

Senior Software Engineer – API

• Define and drive technical strategy for internal tools migration and legacy system transition
• Lead architecture decisions for internal API migration and system modernization
• Design migration patterns, frameworks, and tools that can be reused across the organization
• Establish technical standards and best practices for legacy system decommissioning
• Lead and mentor a squad of backend engineers focused on internal migration
• Collaborate with other squad leads to ensure cohesive platform evolution
• Drive technical decision-making and resolve complex architectural challenges
• Design and execute comprehensive migration strategies for internal tools and systems
• Build compatibility layers and transition bridges for critical internal services
• Coordinate with internal teams to minimize disruption during migration phases

Staff Engineer – Tech Lead

• Drive the technical roadmap for Trust & Safety tools: content detection, workflow automation, moderation, dashboards, and alerting.
• Design and build backend systems using a microservices architecture.
• Design and build API-centric systems using REST, GraphQL, and OpenAPI standards.
• Design and build queuing and event-driven systems.
• Participate in legacy system modernization and incremental migration strategies.
• Proactively propose and implement evolutions and improvements.
• Design pragmatic, high-impact solutions by optimizing resources and prioritizing based on business value.
• Leverage AI to improve automated detection of problematic content (violence, hate, spam, etc.).

Fullstack Tech Lead – Trust & Safety

• Lead a team of front-end and back-end engineers (in-house and external).
• Own and drive the technical roadmap for Trust & Safety tools: content detection, workflow automation, moderation, dashboards, and alerting.
• Design pragmatic, high-impact solutions by optimizing resources and prioritizing based on business value.
• Leverage AI to enhance automated detection of problematic content (violence, hate, spam, etc.).
• Streamline internal processes through automation (workflows, tagging, prioritization, etc.).
• Accelerate development (using tools like Cursor AI, assisted code generation, etc.).
• Collaborate cross-functionally with Product, Data, Legal, and Support teams.
• Ensure the quality, security, and maintainability of deployed tools.

Tech Lead – Trust & Safety

Machine Learning Engineer

• Empowering ML Engineers by providing tools and infrastructure that enhance their productivity while adapting to their specific needs.
• Accelerating time-to-market for the first production-ready versions of ML products by ensuring seamless integration, proper service connections, and access to data and resources.
• Ensuring ML Engineers maintain control over their models in production, allowing them to monitor, troubleshoot, iterate quickly, and refine models and feature engineering logic.
• Facilitating large-scale ML experimentation by providing robust, reproducible, and scalable test environments for data science projects, enabling both qualitative experimentation (internal tests and demos) and quantitative experimentation (A/B testing in production).
• Owning the industrialization and deployment (CI/CD) of ML models , ensuring their reliability, scalability, and performance through advanced MLOps practices.
• Managing model operations and maintenance , guaranteeing optimal performance, monitoring, and continuous improvements in production.

Senior MLOps Engineer

DevOps Engineer

• Build and maintain internal Platform-as-a-Service running on Kubernetes
• Contribute to maintenance and evolution of CD platform based on FluxCD
• Ensure platform reliability and performance through testing, automation and monitoring
• Participate in on-call program, incident management and production troubleshooting
• Ensure optimal use of Kubernetes clusters in AWS (performance and FinOps/cost effectiveness)
• Ensure high level of platform security
• Maintain and improve CD platform and delivery workflows
• Share best practices and collaborate with developers to understand requirements
• Provide guidance on MLOPS and Data architectures (GCP, Airflow, GPUs)
• Maintain detailed documentation of engineering processes, infrastructures, and troubleshooting procedures
• Stay up-to-date with industry trends and drive continuous improvement