CHEP helps move more goods to more people, in more places than any other organization on earth via our 347 million pallets, crates and containers. We employ approximately 13,000 people and operate in 60 countries. Through our pioneering and sustainable share-and-reuse business model, the world’s biggest brands trust us to help them transport their goods more efficiently, safely and with less environmental impact.

What does that mean for you? You’ll join an international organization big enough to take you anywhere, and small enough to get you there sooner. You’ll help change how goods get to market and contribute to global sustainability. You’ll be empowered to bring your authentic self to work and be surrounded by diverse and driven professionals. And you can maximize your work-life balance and flexibility through our Hybrid Work Model .

Job Description

POSITION PURPOSE

Excels in delivery and drives outcomes through solution leadership to contribute and align with Digital Team strategic computer vision initiatives

MAJOR / KEY ACCOUNTABILITIES

• Lead research of nascent computer vision projects including literature review, method evaluation, data collection & exploration, supervision of annotation efforts

• Lead review of established computer vision projects and integrate state-of-the-art research and software to improve performance and deliver new features

• Leverage large image sets to construct and evaluate ML/AI prototypes while minimizing resource requirements

• Optimize computer vision models for deployment on resource-constrained edge systems

• Monitor and fine-tune production ML systems using techniques such as drift monitoring and active learning

• Guide computer vision team discussions by providing insight on potential approaches, assist with troubleshooting and problem solving

• Assess project objectives and tactical plans to ensure successful delivery and provide recommendations to team and project leadership

• Keep current on the latest findings from researchers in relevant computer vision fields

MEASURES

• Successful application of computer vision principles

• Delivery of models that achieve performance benchmarks

• Software and CV models meet team standards for readability, maintainability, and efficiency

AUTHORITY / DECISION MAKING

• Computer vision model selection and optimization

• Working autonomously

KEY CONTACTS

Internal: Computer Vision Chapter Lead, Project stakeholders, other computer vision team engineers

External: Project stakeholders

QUALIFICATIONS

• PhD in Computer Vision, Computer Science, Engineering, or related field

• Expert in using AI, deep learning, and traditional computer vision for facial recognition, person re-id (reidentification) or unique identification of objects

• Expert in the use of model optimization techniques such as quantization, pruning, and knowledge distillation

• Expert level proficiency with computer vision and deep learning toolkits including OpenCV, Pytorch, ONNX, TensorRT

• Expert level proficiency with Python

• Proficient with creation, indexing, and searching embeddings, latent space, and vector representations of data

• Proficient with MLOps tools such as bitbucket/git, DVC, MLflow, JIRA, jupyter, docker

Desirable Qualifications:

• Proficient with multi-node, multi-GPU training of deep neural networks using model and data parallelism

• Proficiency with Go, C/C++

• Proficiency with Tensorflow

EXPERIENCE

• 5+ years of computer vision research and development in industrial or academic settings

• Demonstrated ability to work autonomously and deliver results on schedule

SKILLS AND KNOWLEDGE • Expert in using AI, deep learning, and traditional computer vision for facial recognition, person re-id (reidentification) or unique identification of objects

• Proficient with creation, indexing, and searching embeddings, latent space, and vector representations of data

• Extensive knowledge of fundamental computer vision methods and foundation models

Remote Type

Hybrid Remote

Skills to succeed in the role

Active Learning, Adaptability, C++ Programming Language, Computer Vision, Cross-Functional Work, Curiosity, Data Science, Data Storytelling, Data Visualization, Deep Learning, Digital Literacy, Emotional Intelligence, Empathy, Git, GStreamer, Image Processing, Initiative, Jupyter Notebook, Linux, Machine Learning, Problem Solving, Python (Programming Language)

CHEP Canada invites applications from all qualified individuals. CHEP is committed to fostering workplace diversity, and, provides accommodations to applicants with disabilities throughout our hiring process. If you require this information in alternate format; require communication supports; an accommodation in applying for a posting and/or if you are selected for an interview, please contact our Recruiting Department and a recruiter assigned to the posting will work with you to meet your needs.

We are an Equal Opportunity Employer and we are committed to developing a diverse workforce in which everyone is treated fairly, with respect, and has the opportunity to contribute to business success while realizing his or her potential. This means harnessing the unique skills and experience that each individual brings and we do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state, or local protected class.

Individuals fraudulently misrepresenting themselves as Brambles or CHEP representatives have scheduled interviews and offered fraudulent employment opportunities with the intent to commit identity theft or solicit money. Brambles and CHEP never conduct interviews via online chat or request money as a term of employment. If you have a question as to the legitimacy of an interview or job offer, please contact us at recruitment@brambles.com.