Applied Research Scientist

Sixone Labs develops machine-learning technology for plastics recycling. The Applied Research Scientist builds end-to-end ML systems that turn spectral, hyperspectral, and imaging data into decisions for materials processing, from sensor-data ingestion and model development through deployment in recycling operations.

Responsibilities:

• Build and maintain data pipelines for cameras, optical spectroscopy, and hyperspectral sensors (ingestion, calibration, normalization)
• Develop algorithms for classification, segmentation, anomaly detection, spectral unmixing and representation learning
• Design multimodal models linking sensor data to downstream process outcomes
• Deploy models into production systems
• Establish data quality and calibration standards for sensors
• Design and maintain calibration pipelines for imaging sensors
• Develop preprocessing and feature extraction algorithms
• Handle variations across sensors, lighting conditions, and acquisition setups
• Ensure consistency and traceability between raw sensor data and model inputs
• Establish data quality metrics and validation protocols for sensor outputs
• Work closely with process teams to translate physical signals into model inputs
• Own data experimental designs and statistical evaluations
• Develop data collection requirements and model improvement cycles
• Stay current with spectroscopy, computer vision, and remote sensing literature