Senior Enterprise AI/ML Solutions Engineer

Accenture; Austin (TX); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) plan

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients, 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, data, and choosing models (including Deep Learning, Gen AI, and LLMs).

You will design scalable data and DevOps & MLOps pipelines for training and production, ensure quality and reliability, work with

Qualifications

• Bachelor's degree or equivalent work experience; minimum 12 years total experience.
• 3+ years deploying ML models in production at scale with monitoring and auditing.
• 1+ years distributed computing and cloud deployment experience.
• Experience building AI/ML based software for cloud environments.

Responsibilities

• Formulate real-world problems into scalable AI/ML solutions.
• Develop ML models, data pipelines, and DevOps/MLOps for training and production.
• Customize DL/GenAI/LLM models for business use cases.
• Engage in R&D of new AI algorithms and simulations for client sites.
• Work with large-scale data and ensure high-quality input for training.

Skills

Machine Learning

Model Deployment

DevOps & MLOps

Distributed Computing

Python

C++

Java

R

SQL

Education

Bachelor's degree or equivalent

Tools

Python

C++

Java

R

SQL

Job description

Accenture is seeking an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients, 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, data, and choosing models (including Deep Learning, Gen AI, and LLMs).

You will design scalable data and DevOps & MLOps pipelines for training and production, ensure quality and reliability, work with