ML Scientist, Spectral Imaging for Recycling

Sixone; Burnaby; Vor Ort; CAD 100.000 - 140.000; Vollzeit

Zusammenfassung

Sixone in Burnaby, Canada is building end-to-end ML systems that transform spectral and imaging data into actionable recycling decisions. You will work across the stack—from sensor data ingestion and calibration to model deployment in real-world operations.

This hands-on role emphasizes strong ML fundamentals, with development of multimodal models, data pipelines, and edge deployment. You will collaborate with process teams and stay current with spectroscopy, computer vision, and remote sensing

Qualifikationen

• 2+ years of industry experience in ML engineering or related field.
• Proficient in Python and PyTorch with hands-on model development.
• Experience with high-dimensional data (imaging, spectroscopy, CV, remote sensing).
• Experience with measurement instruments and linking sensor-derived features to physical properties.
• Experience building data pipelines and developing models on cloud infrastructure (AWS).
• Experience in designing ML models (e.g. CNNs, autoencoders) and deploying models on edge devices.

Aufgaben

• 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.

Kenntnisse

Python

PyTorch

High-dimensional data

Cloud AWS

Edge deployment

CNNs

Autoencoders

MLOps

Data pipelines

Tools

Docker

MLflow

CI/CD pipelines

Jobbeschreibung

Sixone in Burnaby, Canada is building end-to-end ML systems that transform spectral and imaging data into actionable recycling decisions. You will work across the stack—from sensor data ingestion and calibration to model deployment in real-world operations.

This hands-on role emphasizes strong ML fundamentals, with development of multimodal models, data pipelines, and edge deployment. You will collaborate with process teams and stay current with spectroscopy, computer vision, and remote sensing