Staff Engineer, Deep Learning (R5180)
Shield AI · Melbourne
- Location
- Melbourne
- Employment
- Internship
- Level
- Staff
- Posted
- 3 months ago
About this role
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Job Description:
Join Our Team: Shape the Future of Perception Technology! 🚀
Are you ready to revolutionize the world of perception capabilities for both autonomous and non-autonomous platforms?
At the forefront of innovation, we are pushing the boundaries of what’s possible, turning cutting-edge insights into real-time, deep-learning-based solutions to solve practical perception challenges on the edge. Your skills will play a key role in driving transformative solutions that redefine the future.
Be part of a dynamic team where innovation meets impact. Let’s shape the future together!
What you'll do:
- Research, design and implement state-of-the-art perception capabilities, taking ideas from conception into world-class field solutions
- Work with and deploy our AI stack to edge devices
- Work in collaboration with the other deep learning engineers to architect and develop tools help to scale up our deep learning operations
- Stay abreast with the literature and actively involve in various R&D project(s)
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
#LI-FB1 #LD
Help us redefine what’s possible in AI-driven perception - apply today! 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.
As published by Shield AI. Applications are handled on their site.
Skills this posting mentions
About Shield AI
Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide.
All 437 openings at Shield AIOne click, then it is written
Apply to Shield AI with a resume written for this role.
Queue Staff Engineer, Deep Learning (R5180) and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Shield AI’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
More roles at Shield AI
See all- 5 weeks ago
- 5 weeks ago
- 5 weeks ago
- 5 weeks ago
- 5 weeks ago
- 5 weeks ago
Similar roles elsewhere
See more- 4 weeks ago
- 4 weeks ago
AI Engineer - FDE (Forward Deployed Engineer)
DatabricksMelbourne, Australia
$75k - $120k/yrMid levelEngineering - 6 weeks ago
Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
500 free credits on sign-up. No card. Nothing is sent until you say so.
Listed from the job board Shield AI publishes. Refolk is not the employer and does not handle their hiring. Applications go to Shield AI directly.