Staff Deep Learning Engineer (R5677)

Shield AI
Melbourne, Australia
On-site

Who this role is best for

Aimed at mid-to-senior level deep learning engineers who can deliver perception solutions and collaborate on AI stack deployment.

Best fit for

  • Mid-to-senior deep learning engineers with 3–5 years of computer vision experience
    — “industry-based experience between 3 – 5 years”
  • Candidates with a strong grasp of deploying AI models on edge devices
    — “Work with and deploy our AI stack to edge devices”
  • Individuals experienced in maintaining and scaling deep learning operations
    — “architect and develop tools help to scale up our deep learning operations”

Things to consider

  • Background checks and possible reference checks are mandatory for all offers
    — “contingent on a cleared background and possible reference check”
  • The role requires active global deployment of technology
    — “technology actively supports operations worldwide”

How to stand out

  • Highlight experience with deploying models in embedded systems during interviews
    — “deploy our AI stack to edge devices”
  • Emphasize contributions to novel deep learning architectures in your resume
    — “implementing novel deep learning network architectures”
  • Showcase publications in top-tier computer vision conferences if available
    — “Publication(s) in world-leading Computer Vision/Artificial Intelligence/Machine Learning conferences/journals”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • delivering deep-learning-based solutions
  • implementing novel deep learning network architectures
  • deploying deep learning models in an embedded production context
  • mentoring junior engineers/researchers
Typical background
PhD in Computer Science or related fieldsindustry-based experience between 3 – 5 years

Skills & requirements

Required

Deep LearningConvolutional Neural NetworksTransformersComputer VisionFoundation ModelsDeep Learning Network ArchitecturesMlops

Preferred

C++PythonObject DetectionTarget TrackingSLAM3D ReconstructionCamera CalibrationBehavior AnalysisVision Language ModelsAutomated Video SurveillanceEmbedded Production ContextStructured And Unstructured PruningNetwork QuantizationPerformance TuningMentoring

Stack & domain

PythonTensorFlowCaffePyTorchConvolutional Neural NetworksTransformersObject ClassificationRecognitionSegmentationFoundation ModelsDeep Learning Network ArchitecturesLeadershipCollaborationDefense-techAutonomy SoftwareAI StackDeep Learning OperationsR&D

About the role

Original posting from Shield AI via Lever

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 

#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.

Source: Shield AI careers (Lever)

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