Senior Machine Learning Engineer
Core
Design, develop, and deploy scalable machine learning solutions in production environments, building end-to-end ML pipelines and distributed data processing workflows.
Role type
Senior IC machine learning engineer (MLOps & production systems)
Builds
Production-grade ML systems, scalable data processing workflows, and containerized ML workloads
Domain
Cloud infrastructure, MLOps, distributed computing
Deliverable
production ML models
Required skills
Python, SQL, PySpark, Scikit-learn, PyTorch, TensorFlow, XGBoost, MLflow, Databricks, AWS, Azure, GCP, Kubernetes, MLOps
Preferred skills
CI/CD pipelines, model monitoring, observability, Docker, workflow orchestration, generative AI/LLMs
Technologies
Kubernetes, Docker, MLflow, Databricks, AWS, Azure, GCP, PySpark
Responsibilities
Design and maintain containerized ML workloads leveraging Kubernetes; Implement MLOps best practices including model versioning and CI/CD; Develop distributed data processing workflows using PySpark and SQL; Deploy and manage ML models across cloud platforms; Build and optimize end-to-end ML pipelines; Drive improvements in model performance and operational efficiency
Seniority
Senior, hands-on IC