Enterprise AI/ML Solutions Engineer

Accenture; Milwaukee (WI); On-site; USD 39,000 - 96,000; Full time

Job summary

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients. You will combine custom models with cloud services, design scalable data pipelines, and ensure reliability of production systems.

Travel 0–100% may be required depending on client needs and engagements. You will work across the full solution lifecycle, from data assessment to model deployment, using Deep Learning, Gen AI, and LLM APIs, with strong collaboration

Qualifications

• Bachelor’s degree or equivalent (min 12 years) work experience; if Associate’s Degree, 6+ years required.
• Minimum 3 years as ML engineer/scientist deploying models in production at scale.
• Minimum 3 years applying CS foundations: architecture, systems engineering, programming.
• Minimum 1 year in distributed computing/big data/cloud engineering.
• Minimum 1 year building and deploying AI/ML software to a cloud environment.

Responsibilities

• Formulate real-world problems into scalable AI/ML solutions.
• Develop and implement ML algorithms and scalable data pipelines for training and production with DevOps & MLOps.
• Customize Deep Learning/Gen AI models for business needs and edge/HPC use cases.
• Engage in R&D of new AI algorithms and simulations for client applications.
• Work with large datasets and apply data preprocessing for high-quality training inputs.
• Maintain efficient data storage/retrieval for models and knowledge.
• Justify model approaches to address business problems.
• Collaborate with business and technical teams to deliver end-to-end projects into production.

Skills

Python

C++

Java

R

SQL

TensorFlow

PyTorch

LLM APIs

Education

Bachelor's degree

MS/PhD preferred

Tools

Docker

Kubernetes

Job description

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients. You will combine custom models with cloud services, design scalable data pipelines, and ensure reliability of production systems.

Travel 0–100% may be required depending on client needs and engagements. You will work across the full solution lifecycle, from data assessment to model deployment, using Deep Learning, Gen AI, and LLM APIs, with strong collaboration