Senior Machine Learning Engineer
Core
Design and implement scalable, production-grade Machine Learning systems in cloud environments, leading end-to-end ML solutions from data ingestion to deployment and monitoring.
Role type
Senior IC machine learning engineer (MLOps & cloud)
Builds
Production ML systems, containerized ML workloads, large-scale data pipelines
Domain
Cloud computing, Data engineering, Artificial Intelligence
Deliverable
production ML models
Required skills
Python, PySpark, Databricks, MLOps, Kubernetes, Docker, Scikit-learn, PyTorch, TensorFlow, XGBoost, SQL
Preferred skills
Healthcare data experience, Deep learning for time series, CI/CD for ML, Kubeflow, KServe, Airflow
Technologies
AWS, Azure, GCP, MLflow, Kubeflow, KServe, Airflow
Responsibilities
Lead design and implementation of scalable ML systems in cloud environments; Architect and deliver end-to-end ML solutions; Design and manage containerized ML workloads using Docker and Kubernetes; Oversee large-scale data pipelines; Lead experimentation strategies including A/B testing and model validation; Drive continuous model improvement through automated retraining and monitoring; Evaluate and prototype emerging AI/ML technologies; Mentor engineers and provide technical leadership.
Seniority
Senior, hands-on IC