Genpact is a global professional services firm that offers digital transformation. Business process management, and consulting services to a wide range of industries. Founded in 1997 as a business unit of General Electric. Genpact has since become an independent company and has expanded its operations to over 30 countries. With a focus on combining process expertise. Technology, and analytics to drive business outcomes. Genpact has established itself as a trusted partner for organizations seeking to improve their operational efficiency. Customer experience, and overall performance.
Responsibilities of the Candidate:
- The AI Engineer’s primary responsibility is to use their expertise to interpret the customer’s business needs and convert them into complex techno-analytic problems.
- They are expected to work collaboratively with a team of specialists to develop and implement large-scale AI solutions that meet the customer’s requirements.
- The core responsibilities of the AI Engineer include designing advanced models capable of processing and analyzing vast amounts of data in various formats, such as textual, numeric, graphic, and speech data.
- Additionally, the AI Engineer is responsible for creating and deploying production-ready code and developing a framework for deploying AI/ML code, ensuring the reliability and robustness of the models used in production.
- Academic coursework and education for the job position listed includes a BTech in Computer Science/Computer Engineering, Information Technology, or Electronics and Communication, as well as coursework in probability and statistics, Bayesian networking, graphical modeling, deep learning, neural networks, and cognitive science.
- Candidates should have completed at least one assignment focused on designing, building, training, and deploying a model for a specific area. Required technology skills include proficiency with statistical toolkits like R, Weka, and Python, with excellent programming skills in Python and/or R, and some experience with Java being an advantage.
- Candidates should also have experience building, deploying, and measuring predictive/prescriptive analytics models using various algorithms like SVM, decision tree, clustering, logistic regression, linear and non-linear regression, ANN, CNN, RNN. Experience with deep learning frameworks such as Tensor Flow, Keras, Torch, and Theano, as well as tooling frameworks like PyCharm or Jupyter is also a plus.
- Online Application Submission
- Online Test- Aptitude Test, Technical Test