Enterprise AI/ML Engineer - Deploy & Scale Models

Accenture; Austin (TX); On-site; USD 83,000 - 165,000; Full time

Job summary

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients. You will work across model selection, data preparation, and scalable DevOps and MLOps pipelines for training and production.

You will apply deep learning, generative AI, and LLMs while ensuring quality, value, and reliability of deployed systems in production across cloud environments.

Qualifications

• Bachelor's degree or equivalent work experience (min 12 yrs).
• 3+ years experience as ML engineer/scientist deploying models in production at scale.
• 3+ years applying CS theory to systems, architecture, and programming.
• 1+ years in distributed compute systems and cloud computing.
• 1+ years building/deploying AI/ML software to cloud environments.

Responsibilities

• Formulate AI/ML solutions for enterprise clients and real-world problems.
• Develop and implement ML algorithms and scalable data pipelines with MLOps.
• Adapt Deep Learning and Gen AI models for diverse use cases.
• Research new AI algorithms and high-performance compute methods for production use.
• Handle large-scale datasets and data preprocessing for training/production.
• Collaborate with business and technical teams to deliver end-to-end projects.

Skills

Python

TensorFlow

PyTorch

LLM APIs

MLOps

DevOps

Distributed computing

Cloud computing

Education

Bachelor's degree or equivalent (min 12 yrs) work exp

MS or PhD in related field (preferred)

Tools

AWS

Docker

Kubernetes

Git

Job description

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients. You will work across model selection, data preparation, and scalable DevOps and MLOps pipelines for training and production.

You will apply deep learning, generative AI, and LLMs while ensuring quality, value, and reliability of deployed systems in production across cloud environments.