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.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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Skills Required
- Deep knowledge of computer vision, machine learning, and deep learning, with strong foundations in mathematics, statistics, optimization, or related disciplines.
- Demonstrated ability to solve open-ended research and engineering problems.
- 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, and ONNX.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Mathematics, Engineering, or a related discipline, or equivalent demonstrated expertise.
- 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 or presentation attack detection, deepfakes, synthetic media, adversarial machine learning, or AI security.
- Red-team or adversarial research experience involving attacks against or stress-testing of machine learning or computer vision systems.
- Familiarity with biometric security and presentation-attack standards such as ISO/IEC 30107.
- Full working rights in Australia.
RELX Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.
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Retirement Support — Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
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Leave & Time Off Breadth — Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.
RELX Insights
What We Do
RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.
