Enterprise AI/ML Scientist — Production-Ready Models

Accenture; Kirkland (WA); On-site; USD 39,000 - 99,000; Full time

Benefits offered by this job

Medical, dental, vision

Life insurance

Long-term disability

401(k) plan

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture in the United States seeks an AI/ML Computational Scientist to design, build, and operationalize AI solutions for enterprise clients, blending custom models with cloud services to deliver production-ready outcomes.

You will architect scalable data and DevOps/MLOps pipelines, tailor Deep Learning and Gen AI models to business needs, work with large datasets, and collaborate with cross-functional teams to deploy end-to-end solutions.

Qualifications

• Bachelor's degree or equivalent work experience (min. 12 years).
• Min 3 years in ML engineering/scientist role deploying models at scale.
• Min 3 years in CS fundamentals, architecture, system engineering, and programming.
• Min 1 year in distributed computing systems and architecture (big data, HPC, cloud).
• Min 1 year building and deploying AI/ML software to a cloud environment.

Responsibilities

• Formulate real-world problems into scalable AI/ML solutions.
• Develop ML algorithms and data pipelines for training and production with DevOps & MLOps.
• Customize Deep Learning and Gen AI models for business use cases.
• Engage in R&D of new AI algorithms, models, and simulations.
• Work with large-scale datasets and preprocessing for high-quality input.
• Implement and maintain data storage/retrieval for models and knowledge.
• Justify the value of model approaches in business problems.
• Collaborate with business and technical teams to deliver end-to-end projects.

Skills

Machine learning

Distributed computing

DevOps & MLOps

Python

C++

Java

R

SQL

TensorFlow

PyTorch

Education

Bachelor's degree or equivalent

MS or PhD preferred

Tools

TensorFlow

PyTorch

Job description

Accenture in the United States seeks an AI/ML Computational Scientist to design, build, and operationalize AI solutions for enterprise clients, blending custom models with cloud services to deliver production-ready outcomes.

You will architect scalable data and DevOps/MLOps pipelines, tailor Deep Learning and Gen AI models to business needs, work with large datasets, and collaborate with cross-functional teams to deploy end-to-end solutions.