À propos de ce poste AI / ML Engineer chez Accenture
Accenture · Sur site · Bengaluru
Project Role : AI / ML Engineer
Project Role Description : 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.
Must have skills : Azure OpenAI Service, API Management, Azure Stack, Python Frameworks, REST API design, OpenAPI/Swagg, Azure Service Bus, Event Grid
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence tools and cloud-based AI services. The role requires managing application pipelines that are suitable for production environments, whether deployed on cloud platforms or on-premises. The engineer integrates generative AI models into solutions and may work on diverse technologies such as deep learning, neural networks, chatbots, and image processing. Collaboration with various teams to ensure seamless implementation and continuous improvement of AI-driven applications is a key aspect of daily activities.
Roles & 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 design and implementation of AI-driven solutions ensuring alignment with project goals.
- Mentor junior team members to enhance their technical skills and project contributions.
- Coordinate cross-functional efforts to optimize AI model deployment and integration.
- Continuously evaluate emerging AI technologies to recommend improvements and innovations.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Azure OpenAI Service, Python Frameworks, API Management, Azure Stack.
- Strong experience in developing and deploying cloud-based AI applications using Microsoft Azure services.
- In-depth knowledge of generative AI models and their practical applications in real-world scenarios.
- Familiarity with building and maintaining scalable application pipelines for production environments.
- Ability to work with deep learning frameworks and neural network architectures.
- Experience in integrating AI solutions with APIs and managing their lifecycle effectively.
Must Need Knowledge In:
Summary:
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence tools and cloud-based AI services. The role requires managing the entire application pipeline, whether deployed on cloud platforms or on-premises, ensuring solutions are production-ready and scalable. The engineer integrates generative AI models into various projects, which may include deep learning architectures, neural networks, conversational agents, and image processing technologies. Collaboration with cross-functional teams to align AI capabilities with business needs and continuous refinement of AI-driven solutions are key aspects of the daily workflow.
Roles & 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 design and implementation of AI-driven solutions ensuring alignment with project goals and quality standards.
- Facilitate knowledge sharing and mentorship within the team to foster professional growth and technical excellence.
- Coordinate with stakeholders to gather requirements and translate them into effective AI application strategies.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Azure OpenAI Service, Python Frameworks, API Management, Azure Stack.
- Strong experience in developing and deploying cloud-native AI applications using Microsoft Azure services.
- In-depth understanding of generative AI models and their practical applications in real-world scenarios.
- Familiarity with deep learning techniques, neural network architectures, and chatbot development.
- Ability to design scalable and maintainable AI pipelines integrating multiple AI and cloud components.
- Experience with image processing and computer vision technologies to enhance AI solution capabilities.
Must Need Knowledge In:
- Azure API Management (APIM), Azure Functions, Logic Apps
REST API design, OpenAPI/Swagger specifications
Azure Service Bus, Event Grid, integration patterns
Security: OAuth2, Entra ID, API gateway policies
Additional Information:
- The candidate should have minimum 5 years of experience in Azure OpenAI Service.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
Additional Information:
- The candidate should have minimum 5 years of experience in Azure OpenAI Service.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
15 years full time education
Project Role Description : 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.
Must have skills : Azure OpenAI Service, API Management, Azure Stack, Python Frameworks, REST API design, OpenAPI/Swagg, Azure Service Bus, Event Grid
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence tools and cloud-based AI services. The role requires managing application pipelines that are suitable for production environments, whether deployed on cloud platforms or on-premises. The engineer integrates generative AI models into solutions and may work on diverse technologies such as deep learning, neural networks, chatbots, and image processing. Collaboration with various teams to ensure seamless implementation and continuous improvement of AI-driven applications is a key aspect of daily activities.
Roles & 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 design and implementation of AI-driven solutions ensuring alignment with project goals.
- Mentor junior team members to enhance their technical skills and project contributions.
- Coordinate cross-functional efforts to optimize AI model deployment and integration.
- Continuously evaluate emerging AI technologies to recommend improvements and innovations.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Azure OpenAI Service, Python Frameworks, API Management, Azure Stack.
- Strong experience in developing and deploying cloud-based AI applications using Microsoft Azure services.
- In-depth knowledge of generative AI models and their practical applications in real-world scenarios.
- Familiarity with building and maintaining scalable application pipelines for production environments.
- Ability to work with deep learning frameworks and neural network architectures.
- Experience in integrating AI solutions with APIs and managing their lifecycle effectively.
Must Need Knowledge In:
Summary:
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence tools and cloud-based AI services. The role requires managing the entire application pipeline, whether deployed on cloud platforms or on-premises, ensuring solutions are production-ready and scalable. The engineer integrates generative AI models into various projects, which may include deep learning architectures, neural networks, conversational agents, and image processing technologies. Collaboration with cross-functional teams to align AI capabilities with business needs and continuous refinement of AI-driven solutions are key aspects of the daily workflow.
Roles & 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 design and implementation of AI-driven solutions ensuring alignment with project goals and quality standards.
- Facilitate knowledge sharing and mentorship within the team to foster professional growth and technical excellence.
- Coordinate with stakeholders to gather requirements and translate them into effective AI application strategies.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Azure OpenAI Service, Python Frameworks, API Management, Azure Stack.
- Strong experience in developing and deploying cloud-native AI applications using Microsoft Azure services.
- In-depth understanding of generative AI models and their practical applications in real-world scenarios.
- Familiarity with deep learning techniques, neural network architectures, and chatbot development.
- Ability to design scalable and maintainable AI pipelines integrating multiple AI and cloud components.
- Experience with image processing and computer vision technologies to enhance AI solution capabilities.
Must Need Knowledge In:
- Azure API Management (APIM), Azure Functions, Logic Apps
REST API design, OpenAPI/Swagger specifications
Azure Service Bus, Event Grid, integration patterns
Security: OAuth2, Entra ID, API gateway policies
Additional Information:
- The candidate should have minimum 5 years of experience in Azure OpenAI Service.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
Additional Information:
- The candidate should have minimum 5 years of experience in Azure OpenAI Service.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
15 years full time education
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
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