Enterprise AI/ML Engineer — GenAI & Production Systems

Accenture; Arlington (VA); On-site; USD 33,000 - 99,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Paid holidays

Job summary

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize enterprise AI/ML solutions. You will combine custom models with cloud and third-party services, covering the full lifecycle from data assessment to production, including Gen AI and large language models.

Role involves developing scalable data and DevOps pipelines, researching new AI algorithms, and collaborating with diverse teams to deliver production-ready outcomes for clients worldwide.

Qualifications

• Bachelor's degree or equivalent and 3+ years of ML engineering/science experience.

Responsibilities

• Formulate real-world problems into scalable AI/ML solutions.
• Develop and implement machine learning models and data pipelines for training and production with DevOps & MLOps.
• Customize Deep Learning and Gen AI models for business needs.
• Engage in R&D of new AI/compute algorithms and simulations for client applications.
• Work with large-scale datasets and perform data preprocessing for model quality.
• Implement and maintain data storage and retrieval for models and knowledge.
• Justify model approaches in business contexts.
• Collaborate with business and technical teams to achieve end-to-end project goals.

Skills

Machine learning

Distributed computing

Cloud environments

DevOps / MLOps

Python

Communication

Education

Bachelor's degree or equivalent

MS or PhD in related field preferred

Tools

TensorFlow

PyTorch

Python

Job description

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize enterprise AI/ML solutions. You will combine custom models with cloud and third-party services, covering the full lifecycle from data assessment to production, including Gen AI and large language models.

Role involves developing scalable data and DevOps pipelines, researching new AI algorithms, and collaborating with diverse teams to deliver production-ready outcomes for clients worldwide.