Machine Learning

Role Overview: As an MLOps Engineer at our company, you will be expected to possess a strong blend of MLOps and ML engineering skills. Your primary responsibilities will revolve around handling tickets related to MLOps and Data Engineering, utilizing your expertise in Python, AWS services (such as ECS, Batch Compute, S3, Timestream, IAM, CloudWatch, Athena), Airflow for orchestration, MLflow for model versioning, GitLab CI, and eventually, AWS SageMaker pipelines. Additionally, you will be required to demonstrate your data engineering skills by expertly monitoring pipelines, investigating query issues, and ensuring smooth data flow from Bulk CDM to ALTO. Key Responsibilities: - Handle MLOps and Data Engineering tickets/development - Utilize Python and various AWS services for orchestration and model versioning - Implement Airflow for orchestration and MLflow for model versioning - Debug forecast and clustering models - Automate CI/CD for ML workflows - Develop and deploy end-to-end ML pipelines - Demonstrate proficiency in ML frameworks like LightGBM Qualifications Required: - Strong experience in MLOps and ML engineering - Proficiency in Python and AWS services - Familiarity with Airflow, MLflow, GitLab CI, and AWS SageMaker pipelines - Expertise in data pipeline monitoring and troubleshooting - Experience in developing and deploying ML pipelines - Background in ML frameworks like LightGBM (Note: The additional details about the company have been omitted as they were not explicitly mentioned in the job description.),