Publicis Re:Sources is the backbone of Publicis Groupe, the world’s most valuable agency group. We are the only full-service, end-to-end shared service organization in the industry, enabling Groupe agencies to do what they do best: innovate and transform for their clients.
Formed in 1998 as a small team to service a few Publicis Groupe firms, Publicis Re:Sources has grown to 6,200+ employees globally. We provide technology solutions and business services including finance, accounting, legal, benefits, procurement, tax, real estate, treasury and risk management.
We continually transform to keep pace with our ever-changing communications industry and thrive on a spirit of innovation felt around the globe. Learn more about Publicis Re:Sources and the Publicis Groupe agencies we support at http://www.publicisresources.com.
The Publicis Re:Sources Guiding Principles define who we are and what we stand for. They reflect the mindset and behaviors that shape how we work, how we support one another, and how we drive progress together.
- People First, Driving Success Together
- Problem Solving Mindset
- Respect Each Other
- Partner and Collaborate as One Team
- Commit to Quality and Standards
- Innovate and Embrace the Future
* Visa Sponsorship is not available for this position including H1b or OPT EAD*
- Collaborate with software engineers, business stake holders and/or domain experts to translate business requirements into product features, tools, projects, AI/ML, NLP/NLU and deep learning solutions.
- Develop, implement, and deploy AI/ML solutions.
- Preprocess and analyze large datasets to identify patterns, trends, and insights.
- Evaluate, validate, and optimize AI/ML models to ensure their accuracy, efficiency, and generalizability.
- Deploy applications and AI/ML model into cloud environment such as AWS/Azure/GCP etc.
- Monitor and maintain the performance of AI/ML models in production environments, identifying opportunities for improvement and updating models as needed.
- Document AI/ML model development processes, results, and lessons learned to facilitate knowledge sharing and continuous improvement.
- Bachelor's or master’s degree in Computer Science, Data Science, Engineering, or a related field.
- Experience on Agentic AI/ Frameworks
- Strong programming skills in languages such as Python, SQL/NoSQL etc.
- Build analytical approach based on business requirements, then develop, train, and deploy machine learning models and AI algorithms
- Exposure to GEN AI models such as OpenAI, Google Gemini, Runway ML etc.
- Experience in developing and deploying AI/ML and deep learning solutions with libraries and frameworks, such as TensorFlow, PyTorch, Scikit-learn, OpenCV and/or Keras.
- Knowledge of math, probability, and statistics.
- Familiarity with a variety of Machine Learning, NLP, and deep learning algorithms.
- Exposure in developing API using Flask/Django.
- Good experience in cloud infrastructure such as AWS, Azure or GCP
- Exposure to Gen AI, Vector DB/Embeddings, LLM (Large language Model)