Senior AI/ML Solutions Engineer

Accenture; Culver City (CA); On-site; USD 54,000 - 162,000; 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 the full lifecycle—from assessing needs and data to selecting models and building scalable pipelines with DevOps and MLOps for production-ready outcomes.

The role covers developing models, data pipelines, and DL/Gen AI customization, plus researching new AI approaches and collaborating with business and technical teams.

Qualifications

• Bachelor's degree or equivalent, with minimum 12 years' work experience (6 years if Associate’s Degree).
• Minimum of 3 years of experience deploying ML models in production at scale.
• Minimum of 3 years of experience in applying theoretical CS foundations including architecture and programming.
• Minimum of 1 year in distributed computing systems and cloud-related computing.
• Minimum of 1 year building and deploying AI/ML software to a cloud environment.

Responsibilities

• Formulate real-world problems into scalable AI/ML solutions.
• Develop ML models, algorithms, and scalable data pipelines for training and production with MLOps.
• Customize DL and Gen AI models for various business use cases.
• Research new AI and HPC algorithms and apply them at client sites.
• Work with large datasets and perform data preprocessing for high-quality training data.
• Collaborate with cross-functional teams to deliver end-to-end production solutions.

Skills

Machine learning

Distributed computing

Cloud deployment

CS fundamentals

Education

Bachelor's degree

Tools

Python

TensorFlow

PyTorch

Java

C++

R

SQL

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 the full lifecycle—from assessing needs and data to selecting models and building scalable pipelines with DevOps and MLOps for production-ready outcomes.

The role covers developing models, data pipelines, and DL/Gen AI customization, plus researching new AI approaches and collaborating with business and technical teams.