Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Expected to be an SME, collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute on key decisions.
Provide solutions to problems for their immediate team and across multiple teams.
Lead the development and implementation of AI models to address complex challenges.
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Locations (2)
Coimbatore, Tamil Nadu, India
Bengaluru, Karnataka, India
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with stakeholders to understand requirements and translate them into technical solutions.
Continuously research and evaluate emerging AI technologies to enhance project outcomes.
Develop applications and systems that utilize AI tools, cloud AI services, and on-prem pipelines with production-ready quality, including generative AI models.
Locations (2)
Pune, Maharashtra, India
Bengaluru, Karnataka, India
Responsibilities
Design and build advanced AI applications
Integrate cloud-based AI services or on-premises pipelines
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Applies GenAI models as part of the solution.
Locations (2)
Indore, Madhya Pradesh, India
Bengaluru, Karnataka, India
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with team members to enhance AI application performance and reliability.
Assist in documenting technical processes and best practices for knowledge sharing.
Requirements
15 years full time education
Nice to have: GenAI models
Nice to have: deep learning
Nice to have: neural networks
Nice to have: chatbots
Skills
AI / ML Engineer
Accenture Infrastructure and Capital Projects, LLC · Posted Nov 9, 2026
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Design and build advanced AI applications and systems
Manage end-to-end application pipelines
Integrate generative AI models into projects
Develop neural network architectures
Implement intelligent systems such as chatbots and image processing tools
Supports Factory of the Future and Industry 4.0 initiatives by leveraging data, analytics, and AI technologies to improve manufacturing efficiency, quality, and operational performance.
Compensation
$90,000 - $125,000 annual compensation
Responsibilities
Leads industry 4.0 and AI initiatives by identifying, prioritizing, and implementing data-driven solutions that optimize manufacturing processes across molding, assembly, and co-extrusion processes.
Collaborates with cross-functional teams including engineering, operations, IT, and automation teams to integrate digital technologies and analytics into production systems.
Develops and maintains data infrastructure including ETL pipelines, databases, SQL queries, and data environments to support manufacturing analytics and AI applications.
Collects, validates, and manages production data from multiple sources, including PLCs, HMIs, sensors, and enterprise systems, ensuring data accuracy and integrity.
Designs, develops, and optimizes machine learning and AI models to improve quality, productivity, predictive maintenance, process control, and operational efficiency.
Requirements
Bachelor's degree in a relevant field such as Computer Science, Engineering, Data Science, or a related discipline.
Nice to have: familiarity with cloud-based analytics platforms (e.g., AWS, Azure)
Nice to have: familiarity with big data technologies (e.g., Hadoop, Spark)