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Senior Generative AI Developer

Cognizant

Chennai, Tamil Nadu, IndiaOn Site

Original Job Summary

Job Summary

The Senior Generative AI Developer will be instrumental in advancing our machine learning capabilities with AWS Machine Learning and AI&ML concepts. Working in a hybrid model, you will develop and deploy scalable solutions using Docker and Kubernetes, driving innovation and enhancing our technological impact on society.

Responsibilities

  • Develop and implement machine learning models using AWS Machine Learning.
  • Collaborate with cross-functional teams to integrate AI&ML concepts.
  • Utilize Docker and Kubernetes for containerization and orchestration.
  • Apply expertise in Amazon Sagemaker for the ML lifecycle.
  • Oversee Terraform use for reliable and repeatable deployments.
  • Maintain code integrity with Git and support collaborative development.
  • Provide technical guidance and mentorship to junior developers.
  • Conduct thorough testing and validation of machine learning models.
  • Implement ML Ops best practices to optimize processes.
  • Translate business needs into technical requirements through stakeholder collaboration.
  • Stay updated with the latest AI and machine learning trends.
  • Ensure compliance with industry standards and data security protocols.
  • Contribute to solutions that positively impact society.

Qualifications

  • Strong background in ML Ops and AWS Machine Learning.
  • Proficiency in Docker and Kubernetes.
  • Hands-on experience with Amazon Sagemaker.
  • Expertise in Terraform and Git.
  • Deep understanding of AI&ML concepts.
  • Strong problem-solving skills and ability to translate complex requirements.

Key Skills/Competency

  • AWS Machine Learning
  • AI&ML
  • Docker
  • Kubernetes
  • Amazon Sagemaker
  • Terraform
  • Git
  • ML Ops
  • Mentorship
  • Compliance

How to Get Hired at Cognizant

🎯 Tips for Getting Hired

  • Research Cognizant's culture: Study mission, values, and employee feedback.
  • Customize your resume: Tailor experience to AWS ML and Docker.
  • Highlight technical skills: Emphasize Kubernetes, Sagemaker, and Terraform.
  • Prepare for interviews: Practice ML Ops and problem-solving scenarios.

📝 Interview Preparation Advice

Technical Preparation

Review AWS Machine Learning services.
Practice Docker containerization setup.
Study Kubernetes orchestration basics.
Explore Terraform scripting samples.

Behavioral Questions

Describe a challenging team project.
Explain your mentoring approach.
Discuss problem-solving in technical scenarios.
Share an experience adjusting to change.