Enterprise AI/ML Solutions Engineer

Accenture; Chicago (IL); On-site; USD 33,000 - 92,000; Full time

Job summary

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize enterprise AI solutions, blending custom models with cloud services to deliver production-ready outcomes across the full lifecycle.

You will work on real-world problems, develop scalable data pipelines with DevOps and MLOps, and tailor Deep Learning and Gen AI models for client needs, collaborating across business, engineering, and design teams to deploy end-to-end solutions.

Qualifications

• Bachelor’s degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)
• Minimum of 3 years of experience as a machine learning engineer or scientist, deploying models in production at scale, including monitoring, alerting, automatic bug filing and auditing.
• Minimum of 3 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming
• Minimum of 1 years of experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks
• Minimum of 1 years of experience in building and deploying AI/ML based software to a cloud environment.

Responsibilities

• Translate real-world problems into scalable AI/ML solutions.
• Develop ML models and data pipelines for training and production with DevOps & MLOps.
• Adapt Deep Learning and Gen AI models for business needs including edge and HPC contexts.
• Research and develop new AI algorithms and apply them to client problems.
• Work with large datasets and perform data preprocessing for high-quality input.

Skills

Python

TensorFlow

PyTorch

Gen AI

Education

Bachelor's degree

MS/PhD preferred

Tools

DevOps

MLOps

Cloud services

Job description

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize enterprise AI solutions, blending custom models with cloud services to deliver production-ready outcomes across the full lifecycle.

You will work on real-world problems, develop scalable data pipelines with DevOps and MLOps, and tailor Deep Learning and Gen AI models for client needs, collaborating across business, engineering, and design teams to deploy end-to-end solutions.