Design, build, and train scalable machine learning models and algorithms for cloud-based environments
Collect, preprocess, and analyze large and complex datasets to support model development and continuous refinement
Transition models from research to production, ensuring they are performant, maintainable, and ready to operate at scale
Deploy ML models into existing or newly developed backend services, integrating seamlessly with cloud infrastructure
Partner closely with engineers and product managers to deliver ML solutions that enhance and support our connected devices
Test, evaluate, and continuously monitor deployed models to ensure accuracy, robustness, and early detection of data drift or performance degradation
Build strong collaborative relationships with technical subject matter experts, stakeholders, and leadership across the organization
Identify, communicate, and manage technical risks throughout the project lifecycle to ensure smooth delivery

2+ years of experience in deploying and optimizing ML models in a production environment using cloud platforms like AWS, GCP, or Azure
Proficiency in ML frameworks (TensorFlow, PyTorch, Scikit-learn) with practical experience in designing and implementing ML models
Proficiency in programming languages such as Python, R, Java, or C++ for developing and optimizing machine learning algorithms
Familiarity with big data technologies and distributed computing frameworks for handling and processing large datasets
Fundamentals of audio and speech signal processing

Machine Learning Engineer – Cloud

Key skills