Sr. Architect

16 hours ago

Mumbai, Maharashtra, India Cognizant Full time ₹ 8,00,000 - ₹ 24,00,000 per year

Job Summary

The Sr. Architect will play a pivotal role in designing and implementing cutting-edge AI and ML solutions using Google Cloud technologies. With a focus on Airflow Vertex AI and MLOps the candidate will drive innovation and efficiency in our AI projects. This hybrid role requires a deep understanding of AI concepts and cloud-based machine learning ensuring robust and scalable solutions.

Responsibilities

  • Lead the design and architecture of AI and ML solutions leveraging Google Cloud technologies to drive innovation and efficiency.
  • Oversee the implementation of machine learning models using Google Vertex AI to ensure scalability and performance.
  • Provide expertise in MLOps to streamline the deployment and monitoring of machine learning models.
  • Collaborate with cross-functional teams to integrate AI solutions into existing systems using Docker and Kubernetes.
  • Develop and maintain CI/CD pipelines for AI projects using Terraform and GIT to ensure seamless updates and deployments.
  • Implement data workflows using Airflow to automate and optimize data processing tasks.
  • Ensure the security and compliance of AI solutions by adhering to industry best practices and company policies.
  • Analyze and interpret complex data sets to provide actionable insights and recommendations.
  • Mentor and guide junior team members to foster a culture of continuous learning and improvement.
  • Evaluate new AI technologies and tools to enhance the companys AI capabilities and offerings.
  • Communicate effectively with stakeholders to align AI initiatives with business objectives and goals.
  • Drive the adoption of AI and ML best practices across the organization to improve overall project outcomes.
  • Monitor and optimize the performance of AI solutions to ensure they meet business requirements.

Qualifications

  • Possess extensive experience in AI and ML concepts with a strong focus on practical applications.
  • Demonstrate proficiency in Google Cloud-Machine Learning and related technologies.
  • Exhibit expertise in containerization and orchestration using Docker and Kubernetes.
  • Show a deep understanding of infrastructure as code using Terraform.
  • Have a strong background in version control systems particularly GIT.
  • Display excellent problem-solving skills and the ability to work collaboratively in a hybrid work model.

Certifications Required

Google Professional Machine Learning Engineer Kubernetes Administrator Certification

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