Responsible AI Engineer

Posted:
8/27/2024, 2:57:58 AM

Location(s):
Pune, Maharashtra, India ⋅ Maharashtra, India

Experience Level(s):
Expert or higher ⋅ Senior

Field(s):
AI & Machine Learning

Project Role : Responsible AI Engineer
Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved.
Must have skills : Machine Learning
Good to have skills : NA
Minimum 2 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary: As an AI/ML Engineer, you will develop applications and systems that utilize AI tools and Cloud AI services. You will be responsible for creating a proper cloud or on-prem application pipeline with production-ready quality. Your role will involve applying GenAI models as part of the solution, and may also include deep learning, neural networks, chatbots, and image processing. Join our team and contribute to cutting-edge AI technology. Roles & 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 the team to understand application requirements. - Design and develop applications based on business process requirements. - Configure applications to ensure optimal performance and functionality. - Test and debug code to identify and resolve any issues. - Collaborate with cross-functional teams to integrate applications with other systems. - Provide technical support and troubleshooting for applications. - Stay updated with the latest industry trends and technologies. - Assist in documenting application design, development, and maintenance processes. Professional & Technical Skills: - Must To Have Skills: Proficiency in Machine Learning. - Strong understanding of statistical analysis and machine learning algorithms. - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. - Solid grasp of data munging techniques, including data cleansing, transformation, and normalization to ensure data quality and integrity - Creation and validation of test data,and predictive modelling like ANN, Gradient Boosting, and K-NN - Knowledge of Predictive analytics and algorithims Additional Information: - 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 742,000 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. We are uniquely able to deliver tangible outcomes because of our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song. These capabilities, 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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Accenture

Website: https://accenture.com/

Headquarter Location: Dublin, Dublin, Ireland

Employee Count: 10001+

Year Founded: 1989

IPO Status: Public

Last Funding Type: Grant

Industries: Business Information Systems ⋅ Construction ⋅ Consulting ⋅ Information Services ⋅ Information Technology ⋅ Infrastructure ⋅ Management Consulting ⋅ Outsourcing