Machine Learning Engineer - - Patient Safety Analytics Engineering

✨ About The Role

- The Machine Learning Engineer will be responsible for the entire ML lifecycle, including data collection, preprocessing, model development, deployment, and monitoring. - The role involves designing, developing, and deploying scalable data pipelines using GCP services such as Dataflow and BigQuery. - The candidate will collaborate with data scientists and machine learning engineers to optimize data for model training and inference. - The position requires the implementation of data quality checks and monitoring systems to ensure data accuracy and reliability. - The engineer will also automate data pipelines and infrastructure using orchestration tools like Apache Airflow.

⚡ Requirements

- The ideal candidate will have at least 2 years of experience as a Machine Learning Engineer, demonstrating a solid understanding of data engineering principles. - Strong programming skills in Python and familiarity with machine learning libraries such as TensorFlow, PyTorch, and scikit-learn are essential. - A deep understanding of various machine learning algorithms and techniques, including regression, classification, clustering, and deep learning, is required. - Experience with data engineering tools and cloud platforms like AWS, GCP, or Azure will be beneficial for success in this role. - Excellent problem-solving, communication, and collaboration skills are necessary to work effectively with cross-functional teams.