AWS MLOps Engineer

Job Description We are seeking a highly skilled AWS MLOps Engineer to join our dynamic team. The ideal candidate will be responsible for managing and optimizing machine learning workflows on AWS, ensuring the effective deployment, scalability, and maintenance of our machine learning models. Key Responsibilities: Design and implement robust MLOps pipelines using AWS services like SageMaker, Lambda, ECS, EKS, and others. Automate machine learning workflows and implement continuous integration and delivery (CI/CD) for ML systems. Monitor and maintain ML models in production, ensuring high performance and scalability. Collaborate with data scientists and engineers to optimize model training, testing, and deployment processes. Implement security best practices for ML operations in the AWS environment. Stay updated with the latest AWS features and machine learning trends to continually improve our systems. Provide technical guidance and support for machine learning operations across the organization. Requirements Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Strong experience in AWS cloud services, specifically with ML services like SageMaker. Proficient in Python, with experience in ML frameworks like Scikit-learn, XGBoost, TensorFlow or PyTorch. Knowledge of Docker, Kubernetes, and other containerization technologies. Experience in building CI/CD pipelines for machine learning. Strong understanding of data engineering and ETL processes. Excellent problem-solving skills and ability to work in a dynamic environment. Preferred Qualifications: AWS certifications related to machine learning or DevOps. Experience in implementing machine learning models in a large-scale production environment. Familiarity with Agile methodologies and tools. Experience with various AWS tools & services including Lambdas, IAM, EC2, Glue, CloudFormation, DynamoDB, CloudFormation. How to Apply: Please submit your resume and cover letter and kindly include examples of previous work or projects related to AWS and machine learning. Benefits We provide a competitive salary and benefits package, a vibrant work environment, and numerous opportunities for professional growth. Youll have the opportunity to work with a team of industry experts on exciting projects that transform businesses and create significant value. Join us to revolutionise the way companies leverage technology for digital transformation. OnebyZero is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Requirements Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Strong experience in AWS cloud services, specifically with ML services like SageMaker. Proficient in Python, with experience in ML frameworks like Scikit-learn, XGBoost, TensorFlow or PyTorch. Knowledge of Docker, Kubernetes, and other containerization technologies. Experience in building CI/CD pipelines for machine learning. Strong understanding of data engineering and ETL processes. Excellent problem-solving skills and ability to work in a dynamic environment. Preferred Qualifications: AWS certifications related to machine learning or DevOps. Experience in implementing machine learning models in a large-scale production environment. Familiarity with Agile methodologies and tools. Experience with various AWS tools & services including Lambdas, IAM, EC2, Glue, CloudFormation, DynamoDB, CloudFormation. How to Apply: Please submit your resume and cover letter and kindly include examples of previous work or projects related to AWS and machine learning.