Machine Learning Engineer
3 weeks ago
Classification: CS-3
Tenure: Continuing
Work Arrangements:
- Due to the nature of the work and operational requirements, this position is eligible for a hybrid work arrangement (combination of working onsite and telework). Employees in this position who telework will be required to travel to the identified work site at least three times per week at their own expense.
We recognize that Indigenous candidates may have important connections to their communities. p>
- While the official location of work for this position will be an NRC facility within Canada, the option of an offsite or a hybrid work arrangement (a combination of working onsite and offsite) may be possible.
As a Computer Vision specialist on the Integrated Omics and Climate Resilience Team at ACRD, you will play a key role in helping position the NRC as leaders in digital research for Canada. Your responsibilities include the delivery of software support for the design, development, and implementation of computer code which enables automated analyses of crop images. Moving from crop phenotype, additional upcoming efforts include contributing to implementing large language models for genomic analyses to elevate gene and allele discovery. The successful candidate will also support data democracy principles at ACRD including important contributions to data management, data platforms, and data science.
Screening CriteriaApplicants must demonstrate within the content of their application that they meet the following screening criteria in order to be given further consideration as candidates:
EducationMasters Science in Computer Science, Electrical Engineering, or a related field.
A Bachelor of Science with 2+ years of experience in the development of computer vision and machine learning algorithms may be considered as an equivalent.
- Significant experience in computer vision approaches with proven track-record of algorithm and code development for image analysis.
- Significant experience and proficiency in programming languages such as Python and C++.
- Experience in computational geometry, 3D representations and data structures.
- Experience in applying neural networks (CNNs, RNNs, VAEs and/or GANs) for computer vision and utilizing deep learning libraries such as TensorFlow or PyTorch.
- Experience working with and analyzing biological images would be considered an asset.
- Experience with transfer learning techniques to leverage pre-trained models, including large foundation models, will be considered an asset.
- Experience with federated learning approaches will be considered an asset.
- Knowledge of traditional computer-vision-related tasks including pre-processing, segmentation, object detection and classification including foundational theory and familiarity with OpenCV and/or other libraries.
- Knowledge of 3D reconstruction techniques and generation of point clouds and other 3D representations.
- Strong knowledge of deep learning algorithms and their applications in computer vision.
- Strong ability in training set generation and data preprocessing, augmentation, and annotation techniques.
- Ability to use version control systems (e.g., li>
- Knowledge of and interest in large language models (e.g., DNA language models) would be considered an asset.
- Practical knowledge of open-source frameworks for federated learning will be considered an asset.
NRC employees enjoy a wide-range of competitive benefits including a robust pension plan, comprehensive health and dental coverage, disability and life insurance, office closure at the end of December, and additional supports to enhance your well-being throughout your career and beyond.
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