Applied Machine Learning Engineer (All Levels)
Core
Design, build, and operate machine-learning models to deliver real business impact across the full ML lifecycle, including data exploration, feature engineering, model building, deployment, and monitoring.
Role type
Applied Machine Learning Engineer (IC)
Builds
Production ML models and ML pipelines for insurance and financial services customers
Domain
Insurance / Financial Services / Machine Learning
Deliverable
production ML models
Required skills
Python, pandas, numpy, scikit-learn, XGBoost, LightGBM, SQL, model evaluation, interpretability (SHAP)
Preferred skills
PyTorch, TensorFlow, Spark, distributed computing, APIs, containers, CI/CD, monitoring, drift detection, MLflow, SageMaker, Azure ML, Docker, AWS, Azure, GCP, deep learning, NLP, computer vision, LLM/RAG
Technologies
Python, pandas, numpy, scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, SQL, Terraform, Java, Typescript, MLflow, SageMaker, Azure ML, Docker, AWS, Azure, GCP
Responsibilities
Support model development, data exploration, testing, and deployments; Build and deploy production ML models; Lead end-to-end ML initiatives and architect ML pipelines
Seniority
Entry to Senior IC