Senior Associate AI/ML Engineer – GCP AI Stack

Title : Senior Associate AI/ML (GCP)

Openings : 2

Top Skills Required :

AI / ML Engineer with GCP AI Tech Stack.

Nice to have – AWS Connect.

GCP AI/ML, Python, Vertex AI, Generative AI/LLMs, RAG, prompt engineering, vector search, ML model deployment/lifecycle management, cloud-native microservices, REST APIs, enterprise integrations, MLOps, and AWS Connect is a plus.

Expected Start Date : ASAP

End Date : 6 months from start date

Location : This position does not require employees to work on-site on a regular basis. However, candidates must reside within a reasonable distance of a Publicis client office (see attached office locations). This requirement is necessary to accommodate in-person interview requests and, if hired, candidates must be able to visit a Publicis client office to collect their company laptop and complete government-issued ID verification.

Interview Process : 1-2 internal video interviews & 1 client round (do onsite interview)

Senior Associate AI/ML Engineer – GCP AI Stack

We are seeking an experienced AI/ML Engineer to design, develop, and deploy scalable AI-powered solutions using the Google Cloud Platform (GCP) AI ecosystem. This role will focus on building enterprise-grade machine learning and Generative AI applications, integrating advanced AI services, and delivering production-ready solutions that drive business value.

The ideal candidate has strong expertise in machine learning, AI application development, and cloud-native architectures, with hands-on experience leveraging GCP's AI and data services. Experience with Amazon Connect (AWS Connect) is a strong plus.

Your Impact:

Design, develop, and deploy AI/ML solutions using the GCP AI technology stack.

Build and operationalize machine learning models and Generative AI applications.

Develop intelligent applications using Large Language Models (LLMs), prompt engineering, and Retrieval-Augmented Generation (RAG) architectures.

Utilize Google Vertex AI and other GCP AI services to train, deploy, monitor, and optimize models.

Develop scalable data pipelines and AI workflows for enterprise applications.

Integrate AI solutions with APIs, databases, and cloud-native services.

Collaborate with product managers, data engineers, architects, and business stakeholders to define AI use cases.

Monitor model performance and implement best practices for MLOps, security, governance, and compliance.

Optimize AI solutions for scalability, reliability, performance, and cost efficiency.

Stay current with emerging AI, ML, and Generative AI technologies.

Skills & Experience

• 5+ years of experience in AI/ML Engineering, Data Science, or Software Engineering.

• Strong programming skills in Python.

• Hands-on experience developing and deploying machine learning applications in Google Cloud Platform (GCP).

• Experience with Vertex AI, AI model deployment, and model lifecycle management.

• Strong understanding of machine learning algorithms, model evaluation, and feature engineering.

• Experience building Generative AI and LLM-based applications.

• Experience with RAG architectures, prompt engineering, and vector search solutions.

• Knowledge of cloud-native application design and microservices-based architectures.

• Experience working with REST APIs and enterprise system integrations.

• Strong problem-solving and communication skills.