Machine Learning Engineer 4 - Intelligent Foundations and Experiences (IFX)
Core
Design, build, and deliver production ML models and components to solve real-world business problems at scale.
Role type
Senior Machine Learning Engineer (Production/Infrastructure)
Builds
Production ML models, optimized data pipelines, and cloud-based ML architectures
Domain
Financial Services / Machine Learning / Cloud Infrastructure
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
Preferred skills
ML algorithm optimization, software development best practices, resilient software design, advanced deployment techniques, incident response planning, various ML techniques (Supervised, semi-supervised, unsupervised, reinforcement learning), model architectures (RNNs, CNNs, LSTMs, Transformers), technical leadership
Technologies
PyTorch, TensorFlow, Spark, Ray, Kubernetes, AWS, GCP, Azure
Responsibilities
Design and build ML models and components for business problems; Inform ML infrastructure decisions; Write and test application code; Collaborate in cross-functional Agile teams; Retrain, maintain, and monitor production models; Build cloud-based architectures; Construct optimized data pipelines; Implement CI/CD best practices; Ensure code management and model governance
Seniority
Senior, hands-on IC