AI/ML Computational Scientist – Production-Scale Solutions

Accenture; Bentonville (AR); On-site; USD 36,000 - 107,000; Full time

Benefits offered by this job

Medical, dental, vision

Life insurance

401(k) plan

Paid holidays

Paid time off

Bonus opportunities

Job summary

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

You will work with Deep Learning, Gen AI, and LLMs, build scalable data and MLOps pipelines, assess client needs and data, and ensure quality, value, and reliability of deployed systems in production environments. Travel may be required.

Qualifications

• Bachelor's degree or equivalent; 12+ years experience if no degree.
• 3+ years as ML engineer/scientist deploying models in production.
• 3+ years in CS theory, architecture, programming.
• 1+ years distributed computing/big data/cloud computing.
• 1+ years building AI/ML software for cloud environments.

Responsibilities

• Formulate real-world problems into scalable AI solutions.
• Develop ML models and data pipelines for training/production with MLOps.
• Customize DL and Gen AI models for business needs.
• Research new AI algorithms and simulations for client use.
• Handle large-scale datasets and preprocessing for training.
• Implement data storage/retrieval for models and knowledge.
• Justify model approaches to business problems.
• Collaborate with cross-functional teams to production.

Skills

Python

Deep Learning

Gen AI

MLOps

Cloud

Data Pipelines

Distributed computing

Model Deployment

Research & R&D

Education

Bachelor's degree

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Spark

Job description

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

You will work with Deep Learning, Gen AI, and LLMs, build scalable data and MLOps pipelines, assess client needs and data, and ensure quality, value, and reliability of deployed systems in production environments. Travel may be required.