Machine Learning Engineer 4
Core
Design, build, and deliver production ML models and components to solve complex business problems at scale.
Role type
Senior IC Machine Learning Engineer (Production/Infrastructure)
Builds
Production-ready ML models, optimized data pipelines, and cloud-based ML architectures
Domain
Financial Services / AI & Machine Learning
Deliverable
production ML models
Required skills
Python, Java, Golang, C++, PyTorch, TensorFlow, Pandas, NumPy, Scikit-learn, Spark, Ray, Kubernetes, AWS, GCP, Azure, CI/CD, model training, hyperparameter tuning, dimensionality reduction, bias/variance analysis, model monitoring, data pipeline construction, Responsible AI practices
Preferred skills
Algorithm optimization, software development best practices, advanced deployment techniques (blue/green, gradual dial-up), incident response planning, deep learning architectures (RNNs, CNNs, LSTMs, Transformers), technical leadership, academic publication
Technologies
PyTorch, TensorFlow, Spark, Ray, Kubernetes, AWS, GCP, Azure, Python, Scala, Java
Responsibilities
Design and deploy ML models for real-world business problems; Inform infrastructure decisions based on modeling techniques; Write and test application code; Collaborate in cross-functional Agile teams; Retrain and monitor production models; Build cloud-based architectures for scaled ML delivery; Construct optimized data pipelines; Implement CI/CD best practices; Ensure code governance and Responsible AI compliance
Seniority
Senior, hands-on IC
