Staff Deep Learning Engineer (R5677)

Job Description:

What you'll do

Required qualifications

• Demonstrable experience in delivering deep-learning-based solutions to solve computer vision problems with industry-based experience between 3 – 5 years
• Strong understanding of using convolutional neural networks and/or transformers for object classification, recognition or segmentation
• Experience working with recent Foundation Models
• Experience with implementing novel deep learning network architectures using existing frameworks (TensorFlow, Caffe, PyTorch or similar)
• Relevant tertiary qualifications (Bachelors/Master/PhD in Computer Science or related fields)

Preferred qualifications

• Publication(s) in world-leading Computer Vision/Artificial Intelligence/Machine Learning conferences/journals (i.e., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, PAMI, JMLR)
• C++ and/or Python development experience
• In-depth understanding of the latest deep learning network architectures for computer vision and image processing
• Experience with any of the following: object detection and target tracking, simultaneous localisation and mapping (SLAM), 3D reconstruction, camera calibration, behaviour analysis, foundation models, vision language models, large multi-modal models, automated video surveillance and related fields
• Experience deploying deep learning models in an embedded production context, including experience of structured and unstructured pruning, network quantization and performance tuning
• Experience in maintaining and/or setting up MLOps systems and services
• Experience in mentoring junior engineers/researchers in the related fields
• #LD
• Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check.
• Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.