- Company Name
- Publicis Re:Sources
- Job Title
- AI/ML Engineer
- Job Description
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**Job Title**
AI/ML Engineer
**Role Summary**
Design, build, and scale generative AI solutions, including large language models (LLMs) and multimodal image generation, using Google Cloud Platform (GCP). Lead technical standards, mentor the team, and ensure production‑grade deployment with robust CI/CD, monitoring, and ethical safeguards.
**Expectations**
- Deliver end‑to‑end GenAI systems that meet business impact objectives.
- Champion best practices in software engineering, code quality, and collaboration.
- Stay current with advancements in GenAI, LLMs, and cloud‑native AI deployment.
**Key Responsibilities**
- Architect, develop, and deploy GenAI workloads (chatbots, content generation, retrieval‑augmented generation, text‑to‑image models).
- Lead model selection, fine‑tuning, and prompt engineering for LLMs and image models.
- Build scalable production deployments on GCP (Vertex AI, BigQuery, custom endpoints).
- Create and maintain CI/CD pipelines for GenAI applications, ensuring seamless releases and runtime monitoring.
- Enforce clean, modular code, comprehensive testing, and thorough documentation.
- Implement rigorous Git workflows (branching, reviews, pull requests) for team collaboration.
- Mentor junior engineers, facilitate knowledge sharing, and support a collaborative environment.
- Apply ethical guidelines, prompt safety, and bias mitigation strategies to all GenAI outputs.
**Required Skills**
- Python programming with deep familiarity with LLM frameworks (OpenAI, HuggingFace, Gemini, Claude).
- Experience in prompt engineering and multimodal models (Stable Diffusion, DALL‑E, Midjourney).
- Hands‑on GCP expertise: Vertex AI, custom endpoint deployment, BigQuery, GenAI APIs.
- Strong Git proficiency: branching, merging, code review, pull request management.
- Software engineering fundamentals: CI/CD, containerization (Docker/Kubernetes), monitoring, and testing of AI systems.
- Knowledge of ethical considerations, prompt safety, and bias mitigation in generative models.
- Excellent communication, leadership, and mentoring capabilities in multidisciplinary teams.
**Required Education & Certifications**
- Master’s degree in Computer Science, Engineering, or related field (PhD preferred).
- Minimum 2–5 years of professional ML/AI development, with proven delivery of GenAI projects.
- Optional: Google Cloud Professional certifications (e.g., Data Engineer, Cloud Architect) may strengthen candidacy.