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 usecases.

Bachelor’s degree in computer science or equivalent work experience required
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.
Demonstrated proficiency in languages like Python or similar languages
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

Associate MLOps Engineer

Key skills