AI/ML Computational Scientist for Scalable Enterprise ML

Accenture

Morristown (NJ)

On-site

USD 39,000 - 107,000

Full time

3 days ago
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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 services, develop end-to-end data pipelines, and ensure reliability of deployed systems. Travel may be required, up to 100% depending on client needs.

The role spans model selection, DevOps/MLOps pipelines, and collaboration with business and technical teams to deliver production-ready outcomes.

Qualifications

  • Bachelor's degree or equivalent (minimum 12 years) work experience.
  • Minimum of 3 years of experience as a machine learning engineer or scientist, deploying models in production at scale.
  • Minimum of 3 years of experience in applying theoretical foundations of computer science, including architecture, system engineering, and programming.
  • Minimum of 1 year of experience in distributed computing systems and architecture that may include big data, HPC, and cloud computing.
  • Minimum of 1 year of experience in building and deploying AI/ML based software to a cloud environment.

Responsibilities

  • Formulate real-world problems into scalable AI/ML solutions.
  • Develop and implement ML algorithms and pipelines for training and production.
  • Customize and apply Deep Learning and Gen AI models per business needs, including edge devices.
  • Engage in R&D of AI algorithms and simulations for client use cases.
  • Work with large-scale data and preprocessing to ensure high-quality input.

Skills

Python
Distributed computing
DevOps & MLOps
Cloud computing
Deep Learning
Gen AI
ML model deployment
Communication

Education

Bachelor's degree or equivalent
MS or PhD in related field preferred

Tools

TensorFlow
PyTorch

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 services, develop end-to-end data pipelines, and ensure reliability of deployed systems. Travel may be required, up to 100% depending on client needs.

The role spans model selection, DevOps/MLOps pipelines, and collaboration with business and technical teams to deliver production-ready outcomes.

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