AI/ML Computational Scientist — Production-Ready AI

Accenture; Columbus (OH); On-site; USD 33,000 - 85,000; Full time

Job summary

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize enterprise AI/ML solutions, combining custom models with cloud and third-party AI services to deliver production-ready outcomes.

Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring

Qualifications

• Bachelor's degree or equivalent; minimum 12 years of work experience (or 6 years with Associate’s Degree)
• Minimum 3 years of experience deploying ML models in production at scale
• Minimum 3 years of experience in CS fundamentals (architecture, systems, programming)
• Minimum 1 year of experience in distributed computing and big data/cloud computing
• Minimum 1 year of experience building AI/ML software for cloud environments

Responsibilities

• Formulate real-world problems into scalable AI/ML solutions
• Develop and implement ML algorithms, models, and data pipelines with DevOps & MLOps
• Customize Deep Learning and GenAI models for various use cases
• Engage in R&D of new AI algorithms and simulations for client projects
• Work with large-scale datasets and data preprocessing for training and production
• Implement and maintain data storage/retrieval for models and knowledge
• Justify model approaches in business contexts
• Collaborate with cross-functional teams to deliver end-to-end projects

Skills

Python

C++

Java

R

SQL

LLM APIs

TensorFlow

PyTorch

Distributed computing

Cloud deployments

Education

Bachelor's degree

MS or PhD preferred

Tools

TensorFlow

PyTorch

Job description

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize enterprise AI/ML solutions, combining custom models with cloud and third-party AI services to deliver production-ready outcomes.

Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring