About Mapped

Mapped is an AI-powered data platform for commercial and industrial spaces that helps property owners, facility operators, and solution providers to rapidly access real-time data from building systems, sensors, devices, and vendor APIs by automating the data discovery, extraction, and normalization process.​ Mapped uses machine learning to abstract the complexities of data integration to create an independent data layer with an open-source data model.

About the role

This role, Software Engineer – Machine Learning System, takes a major role in backend development to fully utilize machine learning (ML) models in production throughout the ML lifecycle, ranging from interactive data collection, deployment of ML models, and monitoring the performance. An ideal candidate will actively work with other data scientists and subject matter experts. 

What you'll do

• Build tools and capabilities for model management, performance monitoring, and data/label management. 
• Build tools and capabilities for end-to-end model deployment pipeline. 
• Coordinate with data scientists to efficiently develop ML models. 
• Coordinate with the DevOps team to follow the best practices in engineering and operation. 

Qualifications

• Must-have Skills  
• • Strong understanding of microservices with REST or gRPC in Python 
  • Strong understanding of data models, preferably in MongoDB 
  • Familiarity with ML lifecycles 
  • Familiarity with preprocessing and parsing text. 
• Good-to-have Skills 
• • Exposure to IoT or building systems 
  • Familiarity with graph data models 
  • Familiarity with ML Frameworks (Azure ML, AWS SageMaker, etc.) 
  • Familiarity with MLOps tools (e.g., Airflow, mlflow, dvc, Feathr, etc.) 
  • Exposure to Large Language Models and prompting design