Computer scientist Jobs in Australia
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Computer scientist • Australia
Last updated: 7 days ago
Senior Software Engineer - Computer Vision
RELXAustralia, The Senior Software Engineer focuses on developing advanced systems to detect and prevent spoofing attacks during biometric authentication processes.
This role involves utilizing machine learning an...Show moreLast updated: 30+ days ago
Supervising Scientist
HealiusTamworth, New South Wales, AU Marius Street, Tamworth NSW 2340.Full Time, Permanent, 38 hours per week.Working hours will be Monday to Friday, with participation in a 7 day on call roster.
Healius has an expansive network of ove...Show moreLast updated: 9 days ago
Field Applications Scientist
Oxford Nanopore TechnologiesAustralia We are looking for a highly driven and motivated individual to join the ANZ TS team as a Field Applications Scientist.This role will suit someone with a strong genomics background and commitment to...Show moreLast updated: 30+ days ago
Computer Engineers (for International Locations)
Countrywide Immigration Private LimitedAustralia, Canada This job posting is for only INTERNATIONAL LOCATIONS.Only serious candidates must apply.Who are prepared to relocate to Canada or Australia or Foreign Countries.
Contact us today for more details : 8...Show moreLast updated: 11 days ago
Data Scientist - South Bank, QLD
Flight Centre Travel GroupAustralia Employer and encourage all suitably qualified applicants to apply, including Aboriginal and Torres Strait Islander People and people from racial, ethnic, or ethno-religious minority groups and peop...Show moreLast updated: 7 days ago
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Senior Software Engineer - Computer Vision
RELXAustralia,30+ days ago
Job descriptionMachine Learning Expertise : In-depth understanding of machine learning frameworks such as TensorFlow, Keras, or PyTorch. Experience in developing deep learning models is essential. Programming Skills : Proficiency in programming languages such as Python, Java, or R for model development and algorithm implementation. Analytical Skills : Strong problem-solving abilities with a solid grasp of statistics, probability theory, and data analysis techniques. Collaboration Skills : Ability to work effectively with cross-functional teams (including data scientists, software engineers, and product managers) to achieve common goals. Experience in similar roles focusing on anti-spoofing or biometric security systems. Bachelor's degree in Computer Science, Mathematics, or a related field. Familiarity with anti-spoofing standards for biometrics such as NIST ISO / IEC 30107 or FIDO. Innovative mindset with a passion for continuous learning and keeping up with the latest advancements in AI and machine learning technologies. We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer : Discounted Health plan rate and Optical Assistance Life assurance and income protection Option to buy additional Annual Leave days Employee Assistance Program Flexible working arrangements Benefits for you and your family Access to learning and development resources
About the Role
The Senior Software Engineer focuses on developing advanced systems to detect and prevent spoofing attacks during biometric authentication processes. This role involves utilizing machine learning and deep learning techniques to create models capable of distinguishing between genuine human interactions and fraudulent attempts.
Please ensure that your resume is kept between 1-2 and a max of 3 pages.
Responsibilities :
- Liveness Detection System Design : Develop and design liveness detection systems that utilize AI algorithms to differentiate between real and fake biometric data. This includes analyzing facial features, eye movements, and other physiological indicators.
- Deep Learning Model Development : Build and optimize deep learning models specifically for liveness detection. This involves selecting appropriate algorithms, conducting experiments, and optimizing model parameters to enhance accuracy and reliability.
- Feature Engineering : Identify and extract features from biometric data that are crucial for detecting spoofing attempts. This includes texture analysis, motion-based detection, and 3D depth analysis.
- Data Collection and Preprocessing : Collaborate with data scientists to collect, clean, and preprocess large datasets required for training liveness detection models. Ensure data integrity and suitability for model development.
- Algorithm Implementation : Implement machine learning algorithms capable of processing real time biometric data to detect inconsistencies indicative of spoofing attempts. This includes integrating multimodal approaches such as facial recognition, fingerprint scanning, and iris recognition.
- System Testing and Validation : Conduct rigorous testing of liveness detection systems to ensure performance in real-world scenarios. Validate models against various spoofing techniques to ensure robustness.
- Monitoring and Maintenance : Deploy liveness detection systems into production environments, ensuring scalability and high performance. Continuously monitor system outputs to identify any issues with accuracy or efficiency.
Requirements :
Working for you
Your recruiter will advise you on the full benefits package for your location