Senior Computer Vision / ML Engineer
Full-time | Australia
About the Business
LexisNexis Risk Solutions helps organizations assess and manage risk across identity verification, fraud prevention, financial crime compliance, credit risk, and customer data management.
About Our Team
IDVerse builds identity verification technology to fight fraud at global scale. Our systems must stay effective against evolving attacks including spoofing, deepfakes, injection attacks, and AI-generated fraud. We are a team of researchers and engineers who think from first principles, experiment rigorously, and invent new approaches as we continuously improve our systems.
What You'll Do
- Research and invent: Investigate difficult problems in computer vision, biometrics, liveness, anti-spoofing, deepfake detection, generative AI, and adversarial attacks. Form hypotheses, run controlled experiments, and develop conclusions that can be trusted. Understand not only whether something works, but why it works, where it fails, and what to try next.
- Red Team Mindset: Develop novel presentation, injection, deepfake, synthetic-media, and AI generated attacks against our systems. Build adversarial evaluations, expose weaknesses, understand their underlying causes, and develop robust defenses.
- Build advanced CV/ML models: Design, train, evaluate, and optimize deep learning approaches across image, video, and multimodal data, applying techniques such as representation learning, transformers, generative models, 3D/geometric vision, where appropriate.
- Own research through production: Take ideas from research and prototyping through benchmarking, optimization, deployment, and real-world evaluation.
- Push the state of the art: Stay close to emerging computer vision and AI research, reproduce and challenge promising ideas, and identify opportunities to turn research advances into meaningful improvements to IDVerse products.
Required qualifications
- Deep knowledge of computer vision, machine learning, and deep learning, backed by strong foundations in mathematics, statistics, optimization, or related disciplines.
- Demonstrated ability to solve open-ended research and engineering problems, rather than only implementing established solutions.
- Strong experience with Python and PyTorch or equivalent modern deep-learning
- frameworks.
- Experience designing controlled experiments, analyzing model behavior and failure modes, and evaluating models against challenging datasets.
- Ability to translate research concepts into efficient, reliable production systems.
- Strong software engineering fundamentals. Experience with C/C++, CUDA, TensorRT, ONNX.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Mathematics,
- Engineering, or a related discipline, or equivalent demonstrated expertise.
Highly Desirable
- PhD or equivalent research experience in computer vision, machine learning, AI, mathematics, or a related field.
- Publications, patents, significant open-source contributions, competition results, or other evidence of original technical or research contributions.
- Experience with biometrics, liveness / presentation attack detection, deepfakes, synthetic media, adversarial ML, or AI security.
- Red-team or adversarial research experience, particularly discovering novel ways to attack, manipulate, or stress-test ML/CV systems.
- Familiarity with biometric security and presentation-attack standards such as ISO/IEC 30107.
Location and collaboration
The team is globally distributed. Candidates must be based in Australia and have full working rights.
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