Publicis Re:Sources is seeking a senior AI/ML Engineer to serve as a Technical Architect, owning end-to-end design and delivery of machine learning solutions to build scalable, secure, and cost-effective AI systems that power high-impact business use cases.
Requirements
- 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.
- Familiarity with a variety of Machine Learning, NLP, and deep learning algorithms.
- Exposure in developing API using Flask/Django.
Responsibilities
- Collaborate with software engineers, business stakeholders 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.
Other
- Bachelor's or master’s degree in Computer Science, Data Science, Engineering, or a related field.
- Good experience in cloud infrastructure such as AWS, Azure or GCP
- Exposure to Gen AI, Vector DB/Embeddings, LLM (Large language Model)
- Visa Sponsorship is not available for this position
- Knowledge of math, probability, and statistics.
