Enterprise AI/ML Solutions Engineer (Production ML)

Accenture; Redmond (WA); Vor Ort; USD 39.000 - 98.000; Vollzeit

Benefits dieser Stelle

Medical, dental, vision benefits

401(k) plan

Bonuses

Zusammenfassung

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 solution lifecycle, from data assessment to model deployment, leveraging Deep Learning, Generative AI, and Large Language Models.

You will develop scalable data pipelines, apply DevOps & MLOps practices, and collaborate with cross-functional teams to deliver production-ready outcomes and measurable business value.

Qualifikationen

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

Aufgaben

• Formulate real-world problems into practical, scalable AI/ML solutions
• Develop and implement ML algorithms, models, and data pipelines with DevOps & MLOps
• Customize DL and Gen AI models for varied use cases based on business needs and data availability
• Engage in R&D of new AI and HPC algorithms and simulations for client use
• Work with large-scale datasets and apply data preprocessing for high-quality training input
• Implement and maintain efficient data storage and retrieval for models and knowledge

Kenntnisse

Python

C++

Java

R

SQL

TensorFlow

PyTorch

Gen AI

LLMs APIs

Ausbildung

Bachelor's degree or equivalent

Jobbeschreibung

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 solution lifecycle, from data assessment to model deployment, leveraging Deep Learning, Generative AI, and Large Language Models.

You will develop scalable data pipelines, apply DevOps & MLOps practices, and collaborate with cross-functional teams to deliver production-ready outcomes and measurable business value.