Advanced AI Engineer

Advanced AI Engineer

Job Description

Join the team behind iconic brands like Huggies®, Kleenex®, Cottonelle®, Scott®, Kotex®, Poise®, Depend®, and Kimberly-Clark Professional®.

 At Kimberly-Clark, it’s all here for you—innovation, growth, and the chance to make a real impact. 

Technology Roles 

You were made to create Better Care for a Better World: designing new technologies, diving into data, optimizing digital experiences, and constantly developing better, faster ways to get results.

You want to be part of a performance culture dedicated to building technology for a purpose that matters.

Here, you’ll work in an environment that promotes sustainability, inclusion, wellbeing, and career development while you help us deliver better care for billions of people around the world.  It starts with YOU. 

About You

In one of our technical roles, you’ll focus on winning with consumers and the market, while putting safety, mutual respect, and human dignity at the center.

Job responsibilities include:

We are seeking an Advanced AI Engineer to design, build, and deploy large‑scale AI and Generative AI systems that drive real business impact.

This role requires deep expertise in machine learning, deep learning, LLMs, and production‑grade AI systems, along with strong software engineering and MLOps skills.

You will work closely with product, platform, and business teams to translate complex problems into scalable AI solutions.

To succeed in this role, you will need the following qualifications:

Required Qualifications

AI & ML Engineering


* Design, develop, and deploy end‑to‑end AI/ML and GenAI solutions across structured and unstructured data.


* Build and fine‑tune Large Language Models (LLMs) using techniques such as fine‑tuning, LoRA/QLoRA, prompt engineering, RAG, agents, and tool‑calling.


* Implement advanced models including transformers, diffusion models, graph ML, time‑series models, and reinforcement learning where applicable.


* Perform model evaluation, bias/fairness checks, explainability (XAI), and continuous performance optimization.

GenAI & Agentic Systems


* Design multi‑agent workflows for complex reasoning, orchestration, and autonomous task execution.


* Build systems leveraging vector databases, embeddings, semantic search, and knowledge graphs.


* Implement guardrails for safety, hallucination reduction, and responsible AI.

MLOps & Platform Engineering


* Productionize AI models using CI/CD pipelines, model versioning, feature stores, and model serving frameworks.


* Deploy scalable solutions on cloud platforms (Azure) using containers and Kubernetes.


* Monitor model drift, performance, cost, and reliability in production environments.

Software & Data Engineering


* Write production‑grade Python code with strong testing, logging, and observability.


* Integrate AI services with enterprise systems via APIs, event‑driven architect...