Data/ML Engg with AWS

Job Summary

Job Description: AWS Data Engineer About the Role We are looking for a highly technical and experienced AWS Data Engineer to join our team. The successful candidate will be responsible for designing, developing, and deploying machine learning models to solve complex business problems by leveraging large datasets on the AWS platform. This role requires working across the entire ML lifecycle, from data collection and preprocessing to model training, evaluation, and deployment using AWS AI Services. The goal is to create efficient self-learning applications capable of evolving over time. If you are passionate about data engineering and machine learning, possess strong programming skills, and have a deep understanding of statistical methods and various ML algorithms, we want to hear from you. Responsibilities Design, develop, and deploy machine learning models on AWS to address complex business challenges. Work across the ML lifecycle, including data collection, preprocessing, model training, evaluation, and deployment using services such as Amazon SageMaker, AWS Glue, and Amazon S3. Leverage large datasets to derive insights and create data-driven solutions using AWS analytics tools. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions on AWS. Optimize and maintain data pipelines and systems on AWS to ensure efficient data processing and storage. Implement and monitor model performance, making necessary adjustments to improve accuracy and efficiency using AWS monitoring tools. Keep up-to-date with the latest advancements in AWS AI and machine learning technologies. Document processes and models to ensure transparency and reproducibility. Preferred Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. Proven experience as a Data Engineer or in a similar role, with a strong focus on machine learning and AWS, ranging from 3 to 8 years of relevant experience. Proficiency in programming languages such as Python, with experience in using AWS SDKs and APIs. Deep understanding of statistical methods and various machine learning algorithms. Experience with AWS AI and ML frameworks and libraries, such as Amazon SageMaker, AWS Glue, and AWS Lambda. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Knowledge of big data technologies and tools, such as Hadoop, Spark, or Kafka, is a plus. Familiarity with AWS cloud platform and services like Amazon EC2, Amazon RDS, and Amazon Redshift is an advantage. Ability to work independently and manage multiple projects simultaneously.