Responsibilities Ensuring that machine learning models are deployed efficiently and reliably into production environments Continuously monitoring the performance of models to detect issues like model drift and ensure they remain accurate and effective Automating the machine learning pipeline, including tasks like data preprocessing, model training, and evaluation Working closely with data scientists, software engineers, and IT operations to integrate machine learning models into business processes Managing version control for models and ensuring compliance with governance policies Identifying and implementing ways to improve the performance and scalability of ML systems Exploring cloud tools and technologies that assist data science with implementing their use cases Requirements Bachelor’s degree in computer science or equivalent work experience Minimum of 2 years experience in software engineering and analytics technology (academic experience included) Experience handling large datasets to build data pipelines Experience writing SQL and using data visualization tools Experience solving complex problems and independently developing solutions Proficiency in languages such as Python or similar Strong understanding of data processing and storage solutions Ability to troubleshoot issues in ML models and infrastructure Ability to work independently with minimal supervision or function in a team environment sharing responsibility, roles, and accountability Excellent oral and written communication skills Strong interpersonal and organizational skills Tools & Technologies Cloud tools Data visualization tools Version control Governance policies Python SQL Data pipelines, data processing, data storage #J-18808-Ljbffr
