Data & AI/ML Engineer (AWS Ecosystem)

Role Overview: As a talented Data & AI/ML Engineer with strong hands-on experience in the AWS ecosystem, you will be responsible for working on exciting data and machine learning projects. Your role will involve building pipelines, deploying models, and leveraging AWS services to deliver scalable solutions. Key Responsibilities: - Data Engineering: Execute ETL processes, perform data modeling, and work with tools such as AWS Glue, Spark, and Airflow. - Machine Learning: Implement machine learning algorithms using SageMaker, TensorFlow, PyTorch, and Scikit-learn. - AWS Services: Utilize Redshift, S3, Lambda, EC2, Kinesis, and IAM for various tasks. - Programming: Proficient in Python and SQL for developing and maintaining code. - Additional Skills: Familiarity with CI/CD, Docker, and Terraform would be beneficial. Qualifications Required: - 3-5+ years of experience in Data or ML Engineering. - Strong understanding of AWS cloud services. - Hands-on experience with AI/ML model deployment or data pipelines. - Proactive problem solver with a penchant for end-to-end ownership. Please note that no additional details about the company were provided in the job description. Role Overview: As a talented Data & AI/ML Engineer with strong hands-on experience in the AWS ecosystem, you will be responsible for working on exciting data and machine learning projects. Your role will involve building pipelines, deploying models, and leveraging AWS services to deliver scalable solutions. Key Responsibilities: - Data Engineering: Execute ETL processes, perform data modeling, and work with tools such as AWS Glue, Spark, and Airflow. - Machine Learning: Implement machine learning algorithms using SageMaker, TensorFlow, PyTorch, and Scikit-learn. - AWS Services: Utilize Redshift, S3, Lambda, EC2, Kinesis, and IAM for various tasks. - Programming: Proficient in Python and SQL for developing and maintaining code. - Additional Skills: Familiarity with CI/CD, Docker, and Terraform would be beneficial. Qualifications Required: - 3-5+ years of experience in Data or ML Engineering. - Strong understanding of AWS cloud services. - Hands-on experience with AI/ML model deployment or data pipelines. - Proactive problem solver with a penchant for end-to-end ownership. Please note that no additional details about the company were provided in the job description.