Lead Data Scientist - ML for Smart Recycling

Sixone Labs; Burnaby; Vor Ort; CAD 110.000 - 170.000; Vollzeit

Zusammenfassung

Sixone Labs is seeking a data science leader to drive real-time sorting and process decisions using high-dimensional sensor data. You will guide a team of data scientists and ML engineers, with 65% hands-on work and 35% leadership, delivering scalable ML systems from research to production.

You will architect models, manage data pipelines on AWS, and mentor the team while collaborating with Engineering, R&D, and Production to deploy robust solutions for recycling insights.

Qualifikationen

• 4+ years in data science or applied ML research with focus on computer vision or spectral/sensor data.
• Demonstrated technical leadership; project ownership or tech lead experience preferred.
• Advanced degree or equivalent practical experience in a quantitative field.
• Deep experience with representation learning on high-dimensional sensors and preprocessing/calibration.
• Strong Python and SQL; experience deploying models to production.
• Hands-on PyTorch experience and CV libraries; Docker, CI/CD, and experiment tracking.

Aufgaben

• Lead architectural decisions for ML systems translating product requirements into scalable designs.
• Develop and benchmark deep learning architectures for high-dimensional spectral data.
• Build and manage data pipelines in Python and SQL, on AWS, integrating diverse data sources.
• Mentor and grow a team of data scientists and ML engineers; set technical direction.
• Collaborate with Engineering, R&D, and Production to move models from lab to production.

Kenntnisse

Data science

Leadership

Python

SQL

PyTorch

Computer Vision

Sensor data

ML pipelines

OpenCV

AWS

Docker

MLflow

ONNX

TensorRT

Ausbildung

Master's or Ph.D. in Computer Science, Electrical Engineering, Physics, or related quantitative field

Tools

PyTorch

Docker

MLflow

OpenCV

TensorRT

ONNX

AWS

SQL

Python

Jobbeschreibung

Sixone Labs is seeking a data science leader to drive real-time sorting and process decisions using high-dimensional sensor data. You will guide a team of data scientists and ML engineers, with 65% hands-on work and 35% leadership, delivering scalable ML systems from research to production.

You will architect models, manage data pipelines on AWS, and mentor the team while collaborating with Engineering, R&D, and Production to deploy robust solutions for recycling insights.