Job Description
Company description Publicis Groupe is the largest Communications Group worldwide and the leader in Digital and Interactive Communications. Publicis has activities spanning 108 countries on five continents and employs approximately 72,000 professionals worldwide. Publicis Groupe offers local and international clients a complete range of communication services through the nearly 1,400 agencies across our four global networks, including: Publicis Re:Sources Re:Sources is the shared services provider of Publicis Groupe, delivering a suite of multi-tenant managed and professional services to Publicis Groupe agencies worldwide, in support of key Groupe business operations. Those operations include: Information Technology & Technology Solutions, Finance, Legal, Procurement, Real Estate, Insurance and other services to our business units Overview The AI/ML Architect shapes the AI strategy and leads enterprise-level architecture for multimodal AI in the media organization. This includes building capabilities across media understanding, LLM workflows, multimodal RAG, real-time metadata enrichment, content intelligence, personalization, and scalable AI platform infrastructure. Responsibilities Detailed Responsibilities Enterprise Architecture & Strategy Define long-term AI architecture roadmap across: NLP, CV, ASR, video AI Multimodal LLMs Recommendation systems Content moderation & compliance RAG & knowledge systems Agentic automation Architect scalable ingestion pipelines for high-volume media (10K+ hours of video). Define standards for model lifecycle, governance, auditability, and lineage. Platform & Infrastructure Architect GPU clusters, distributed compute, and cloud AI platforms. Oversee integrations of: Media Asset Management (MAM) Content Management Systems (CMS) Data lake/lakehouse Vector databases Observability platforms Governance & Compliance Ensure compliance with: Content safety guidelines Copyright/IP protection Data privacy laws Responsible AI standards (NIST AI RMF) Innovation & Leadership Evaluate emerging multimodal and generative AI technologies. Drive adoption of LLMOps practices and agentic AI frameworks. Present architecture strategies to C-level stakeholders. Must-Have Skills Deep expertise in multimodal AI (text–image–audio–video). Mastery of LLMs and their ecosystem (fine-tuning, adapters, vector search). Expert-level cloud architecture (Azure/AWS/GCP). Strong experience in enterprise-scale MLOps + LLMOps. Deep exposure to media processing at scale. Preferred skills Knowledge of video generation, audio synthesis, and generative media workflows. Experience in building AI COEs or platform teams. Qualifications 10+ years in AI/ML with at least 3+ years architecting enterprise systems. Master’s/Ph.D Additional information Work Schedule Core work hours are Monday through Friday, 9:00 AM-5:00 PM. Must also be flexible and be available to work non-standard business hours upon request or as needed Must be available via cell phone for VIP support Travel Local travel between sites may be required Occasional travel to sites outside the local area may be required Salary Range: Transparency matters to us. The salary range for this position is $124000-$204000 per year. Actual compensation within this range will be based on a variety of factors, including relevant experience, knowledge, skills, and applicable certifications. This range reflects what we reasonably expect to offer based on current market data. Job description only reflects management’s assignment of essential functions. Management reserves the right to assign or reassign duties and responsibilities to this job at any time. This job description in no way states or implies that these are the only duties to be performed by the employee(s) currently in this position. Employee(s) will be required to follow any other job related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. A review of this position has excluded the marginal functions of the position that are incidental to the performance of fundamental job duties. All duties and responsibilities are essential job functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the incumbent(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an "at-will" relationship. Re:Sources USA is an Equal Opportunity / Affirmative Action employer. All qualified applicants to Re:Sources USA will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status.
10+ years in AI/ML with at least 3+ years architecting enterprise systems. Master’s/Ph.D
Detailed Responsibilities Enterprise Architecture & Strategy Define long-term AI architecture roadmap across: NLP, CV, ASR, video AI Multimodal LLMs Recommendation systems Content moderation & compliance RAG & knowledge systems Agentic automation Architect scalable ingestion pipelines for high-volume media (10K+ hours of video). Define standards for model lifecycle, governance, auditability, and lineage. Platform & Infrastructure Architect GPU clusters, distributed compute, and cloud AI platforms. Oversee integrations of: Media Asset Management (MAM) Content Management Systems (CMS) Data lake/lakehouse Vector databases Observability platforms Governance & Compliance Ensure compliance with: Content safety guidelines Copyright/IP protection Data privacy laws Responsible AI standards (NIST AI RMF) Innovation & Leadership Evaluate emerging multimodal and generative AI technologies. Drive adoption of LLMOps practices and agentic AI frameworks. Present architecture strategies to C-level stakeholders. Must-Have Skills Deep expertise in multimodal AI (text–image–audio–video). Mastery of LLMs and their ecosystem (fine-tuning, adapters, vector search). Expert-level cloud architecture (Azure/AWS/GCP). Strong experience in enterprise-scale MLOps + LLMOps. Deep exposure to media processing at scale. Preferred skills Knowledge of video generation, audio synthesis, and generative media workflows. Experience in building AI COEs or platform teams.