Machine Learning / MLOps Engineer

As an MLOps Engineer at our Bangalore location, you will play a pivotal role in designing, developing, and maintaining robust MLOps pipelines for generative AI models on AWS. With a Bachelor's or Master's degree in Computer Science, Data Science, or a related field, you should have at least 2 years of proven experience in building and managing MLOps pipelines, preferably in a cloud environment like AWS. Your responsibilities will include implementing CI/CD pipelines to automate model training, testing, and deployment workflows. You should have a strong grasp of containerization technologies such as Docker, container orchestration platforms, and AWS services like SageMaker, Bedrock, EC2, S3, Lambda, and CloudWatch. Practical knowledge of CI/CD principles and tools, along with experience working with large language models, will be essential for success in this role. Additionally, your role will involve driving technical discussions, explaining options to both technical and non-technical audiences, and ensuring software product cost monitoring and optimization. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow, familiarity with generative AI models, and experience with infrastructure-as-code tools like Terraform or CloudFormation will be advantageous. Moreover, knowledge of model monitoring and explainability techniques, various data storage and processing technologies, and experience with other cloud platforms like GCP will further enhance your capabilities. Any contributions to open-source projects related to MLOps or machine learning will be a valuable asset. At CGI, we believe in ownership, teamwork, respect, and belonging. Your work as an MLOps Engineer will focus on turning meaningful insights into action, with opportunities to develop innovative solutions, build relationships with teammates and clients, and access global capabilities to scale your ideas. Join us in shaping your career at one of the largest IT and business consulting services firms globally.,