Enterprise AI/ML Scientist - Deploy & Scale Gen AI

Accenture; Irving (TX); On-site; USD 83,000 - 179,000; Full time

Benefits offered by this job

Health insurance

Dental plan

Vision plan

Life insurance

401(k) plan

Paid time off

Job summary

Accenture is hiring an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients. You will work on Deep Learning, Gen AI, and large language models, creating scalable data and DevOps/MLOps pipelines for training and production.

The role spans the full lifecycle from data assessment to production deployment, with travel as needed. A strong foundation in Python and ML frameworks is required.

Qualifications

• Bachelor's degree or equivalent work experience (minimum 12 years).
• Minimum of 3 years of experience as a machine learning engineer or scientist.
• Experience deploying models in production at scale.
• Experience in distributed computing systems and cloud environments.
• Experience building and deploying AI/ML based software to a cloud environment.

Responsibilities

• Formulate real-world problems into scalable AI and ML solutions.
• Develop ML models and scalable data pipelines for training and production with DevOps & MLOps.
• Customize Deep Learning and Gen AI models for business needs across data availability and infrastructure.
• Engage in R&D of new AI and high-performance compute algorithms and simulations.
• Work with large-scale datasets and apply data preprocessing for high-quality inputs.
• Implement and maintain data storage/retrieval for models and knowledge.
• Justify the value of model approaches in business problems.
• Collaborate with cross-functional teams to production delivery.

Skills

Machine Learning

Python

Distributed Computing

DevOps / MLOps

Education

Bachelor's degree

MS or PhD preferred

Tools

TensorFlow

PyTorch

LLM APIs

Job description

Accenture is hiring an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients. You will work on Deep Learning, Gen AI, and large language models, creating scalable data and DevOps/MLOps pipelines for training and production.

The role spans the full lifecycle from data assessment to production deployment, with travel as needed. A strong foundation in Python and ML frameworks is required.