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Sixone

Lead Data Scientist

Burnaby, BC, Canada

$110,000 to $170,000 CAD / year · Full-time

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Job details

Pay: $110,000 to $170,000 CAD / year
Job type: Full-time
Apply by: Dec 9, 2026
Posting language: English
Posted: Nov 9, 2026

Original job description

Company

Sixone’s mission is to enable a world where blended plastics products can be circularly recycled back into existing supply chains instead of being sent to landfill. Sixone is developing technologies to enable advanced recycling of blended plastics and plastic-based products. The company’s technology applies process digitalization and advanced analytics to build a depolymerization reactor tailored to enable efficient plastics recycling. The company aims to fundamentally change the economics behind current recycled materials through advanced processing and materials technologies.

Overview of Role

This role focuses on applying data science and machine learning techniques to make real-time sorting and process decisions. You will lead a small team of talented data scientists to build robust representations of materials from high-dimensional sensor data, and turning them into models that run reliably.

This is a hybrid role that requires a consistent in-office presence four days per week.

Responsibilities

Lead architectural decisions for Sixone’s ML systems by translating scientific and product requirements into scalable, maintainable system designs.
Develop and benchmark novel deep learning architectures for high-dimensional spectral data, including classification, segmentation, anomaly detection, and representation learning.
Build and manage data pipelines in Python and SQL, locally and on AWS, integrating data from a variety of imaging and edge-sensing devices, including proprietary formats and calibration workflows.
Lead, mentor, and grow a team of data scientists.
Drive work planning, prioritization, and resource allocation against short- and long-term objectives.
Partner with Engineering, R&D, and Production teams to move models from lab to pilot to production scale.
Maintain documentation standards for experiments, data workflows, and models that support IP protection, compliance, and knowledge retention.
Stay current with the state of the art in ML for sensing and imaging, and bring relevant methods into the team.

Candidate Requirements

4+ years in data science or applied ML research with a focus on computer vision or spectral/sensor data
Demonstrated technical leadership
Master's or Ph.D. in Computer Science, Electrical Engineering, Physics, or a related quantitative field or equivalent practical experience.
Experience with representation learning on high-dimensional sensors: autoencoders, self-supervised learning, dimensionality reduction, and sensor preprocessing/calibration.
Experience in Python and SQL, with a track record of taking models from research prototype to production.
Hands-on PyTorch experience (CNNs, Vision Transformers, and autoencoders) and computer vision libraries such as OpenCVPractical experience with pytest, Docker, CI/CD pipelines, and experiment tracking (MLflow or similar)
Effective communication skills with both technical and non-technical stakeholders.
Legally entitled to work in Canada.

Preferred Skills

Hyperspectral imaging experience: spectral unmixing, band selection, sensor calibration, HSI data formats.
NIR/SWIR spectroscopy or chemometrics
Multi-sensor fusion; edge/real-time deployment (ONNX, TensorRT, embedded inference).
ML for industrial inspection, sorting, or manufacturing systems.

Sixone offers a stimulating work environment that promotes creativity, curiosity, and innovation. Join the team and contribute to our mission to transform the recycling industry and promote a sustainable future!

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More about this job

Responsibilities

Lead the design and development of machine learning systems for real-time sorting and process decisions, including deep learning models for high-dimensional spectral and sensor data. Manage and mentor a data science team, build data pipelines, and partner with engineering, R&D, and production teams to deploy models from the lab through pilot and production environments.

Requirements

Requires at least four years of data science or applied machine learning experience focused on computer vision or spectral/sensor data, along with demonstrated technical leadership and a master's degree, Ph.D., or equivalent practical experience in a quantitative field. Candidates should have hands-on Python, SQL, PyTorch, computer vision, testing, Docker, CI/CD, and production model experience, and must be legally entitled to work in Canada.

Skills

Data Science
Machine Learning
Deep Learning
Computer Vision
High-Dimensional Sensor Data
Spectral Data Analysis
Representation Learning
Python
SQL
PyTorch
OpenCV
Data Pipelines
AWS
Team Leadership
Model Deployment
Sensor Calibration

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Data Science
Deep Learning
Computer Vision
Spectral Data
Hyperspectral Imaging
NIR/SWIR Spectroscopy
Chemometrics
Representation Learning
Self-Supervised Learning
Autoencoders
Dimensionality Reduction
Sensor Preprocessing
Sensor Calibration
Multi-Sensor Fusion
Python
SQL
PyTorch
CNNs
Vision Transformers
OpenCV
AWS
Docker
Pytest
CI/CD
MLflow
ONNX
TensorRT
Edge Deployment
Industrial Inspection

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