Machine Learning Engineer, Underwriting

Bree
United States
Workplace: RemoteFull timeUSD 130,000 - 230,000 annuallyFunction: Data Science & Machine LearningSkills: ["Problem-solving","Analytical thinking","Collaboration","Ownership"]

Design, deploy, and scale end-to-end machine learning pipelines and MLOps for underwriting decisions. Work with structured and unstructured data, deploy models on cloud platforms with containerization, ensure monitoring and explainability, and collaborate with data engineers to deliver production-ready AI solutions that power Bree's fintech platform.

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FursaFursa
Bree
Bree
3 months ago

Machine Learning Engineer, Underwriting

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 9 hours agoStatus: Live

Job Summary

Design, deploy, and scale end-to-end machine learning pipelines and MLOps for underwriting decisions. Work with structured and unstructured data, deploy models on cloud platforms with containerization, ensure monitoring and explainability, and collaborate with data engineers to deliver production-ready AI solutions that power Bree's fintech platform.
Location: United States
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design, develop, and deploy end-to-end machine learning pipelines, ensuring efficiency in training, validation, and inference.
  • •Implement MLOps best practices, including CI/CD for ML models, model versioning, monitoring, and retraining strategies.
  • •Optimize ML models using feature engineering, hyperparameter tuning, and scalable inference techniques.
  • •Collaborate with data engineers to develop high-performance data pipelines for training and inference.
  • •Deploy and manage models on cloud platforms (AWS, GCP, Azure) with containerization and orchestration tools like Docker and Kubernetes.

Pay and Benefits

Salary: USD 130,000 - 230,000 annually
Perks:Health InsuranceDentalVisionLearning BudgetHome OfficeWellness StipendMeal AllowanceCommuter BenefitsPaid ParentalPaid Leave

Key Requirements

  • •Proficiency in Python with experience in ML libraries such as Scikit-Learn, LightGBM, and PyTorch.
  • •Experience with MLOps tools (MLflow, Kubeflow, or SageMaker) for tracking experiments and automating workflows.
  • •Hands-on experience with data manipulation libraries (Pandas, NumPy) and databases (SQL, NoSQL).
  • •Knowledge of deploying ML models to cloud platforms (AWS, GCP, Azure) and managing infrastructure with Docker and Kubernetes.
  • •Ability to design real-time and batch inference pipelines and maintain model performance with monitoring and explainability.
Experience:FintechConsumer finance
Skills:Problem-solvingAnalytical thinkingCollaborationOwnership
Languages:English
Tech Stack:PythonScikit-learnLightGBMPyTorchMLflowKubeflowSageMakerPandasNumPySQLNoSQLAWSGCPAzureDockerKubernetes

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Bree
Develops Bree, an AI-powered writing assistant that helps individuals and teams generate, edit, and optimize emails, marketing copy, and short-form content to save time and improve messaging consistency.
Industry: AI & Machine Learning
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
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