What would you do? You will be part of the Technology for Operations team that acts as a trusted advisor and partner to Operations. The team provides innovative and secure technologies to help clients build an intelligent operating model, driving exceptional results. We work closely with the sales, offering and delivery teams to identify and build innovative solutions.
The Tech For Operations (TFO) team provides innovative and secure technologies to help clients build an intelligent operating model, driving exceptional results. Works closely with the sales, offering and delivery teams to identify and build innovative solutions. Major sub deals include AHO(Application Hosting Operations), ISMT (Infrastructure Management), Intelligent Automation
Understanding of foundational principles and knowledge of Artificial Intelligence AI including concepts, techniques, and tools in order to use AI effectively.
 

What are we looking for?

 •Machine Learning
•Machine Learning Algorithms
•Microsoft Azure Machine Learning
•Python (Programming Language)
•Python Software Development
•Ability to work well in a team
•Written and verbal communication
•Numerical ability
•Results orientation

•1 CL8 AI Research Scientists
1. Deep Expertise in Machine Learning & AI Theory
2. Algorithm Design & Theoretical Innovation
3. Data Proficiency & Synthetic Data Generation
4. Responsible AI & Ethical Awareness
5. Programming & Tooling
 

Proficiency in:
Python, TensorFlow, PyTorch, and JAX
Cloud-based AI platforms (e.g., Azure OpenAI, AWS SageMaker)
Version control, containerization (Docker), and MLOps pipelines
The Azure OpenAI Service L100 deck also emphasizes the evolution of tooling from symbolic AI to modern generative models 6.
6. Collaboration & Communication
AI Research Scientists often work in interdisciplinary teams and must:

Publish research
Present at conferences
Collaborate with engineers, product teams, and stakeholders
2 CL8 ML Research Engineers:
1. Mathematical & Statistical Foundations
2. Programming & Software Engineering
3. Model Development & Experimentation
4. MLOps & Deployment
5. Data Engineering & Feature Engineering
ML Research Engineers must be adept at:

Data 
 

Roles and Responsibilities: 

•In this role you are required to do analysis and solving of moderately complex problems
• Typically creates new solutions, leveraging and, where needed, adapting existing methods and procedures
• The person requires understanding of the strategic direction set by senior management as it relates to team goals
• Primary upward interaction is with direct supervisor or team leads
• Generally interacts with peers and/or management levels at a client and/or within Accenture
• The person should require minimal guidance when determining methods and procedures on new assignments
• Decisions often impact the team in which they reside and occasionally impact other teams
• Individual would manage medium-small sized teams and/or work efforts (if in an individual contributor role) at a client or within Accenture
• Please note that this role may require you to work in rotational shifts