Machine Learning Engineer
Core
Develop large-scale distributed machine learning systems, optimize feature extraction and transformation, and manage Feature Stores for reusability across ML pipelines.
Role type
Senior Machine Learning Engineer (MLOps & Platform)
Builds
Scalable, performant, and reliable machine learning systems and platforms
Domain
Machine Learning / MLOps / Predictive Analytics
Deliverable
production ML models
Required skills
supervised and unsupervised learning, survival analysis, time series modeling, statistical forecasting, behavioral data modeling, model training, versioning, monitoring, MLOps practices, CI/CD, Docker, Kubernetes, Airflow, SageMaker, MLflow, feature stores
Preferred skills
business-oriented mindset, ability to connect model outcomes to product and strategic goals
Technologies
TensorFlow, PyTorch, Scikit-Learn
Responsibilities
Develop large-scale distributed machine learning systems, collaborate with cross-functional teams to deploy/integrate models, liaise with Business Units for ML needs, optimize feature extraction and transformation, manage Feature Stores, ensure scalability and cost efficiency of the ML platform, evaluate and adopt new technologies
Seniority
Senior, hands-on IC