Dilpreet Singh Email & Phone Number
Who is Dilpreet Singh? Overview
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Dilpreet Singh is listed as Lead Machine Learning Engineer at IP Australia, a with 906 employees, based in Melbourne, Victoria, Australia. AeroLeads shows a matched LinkedIn profile for Dilpreet Singh.
Dilpreet Singh previously worked as Machine Learning Lead at Ip Australia and Lead Machine Learning Engineer at Raedyne Systems. Dilpreet Singh holds Honours Degree, Computer Science from Monash University.
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About Dilpreet Singh
I am a highly motivated and experienced machine learning engineer, with over 8 years of experience in the field. I take pride in developing production-ready solutions to tough challenges and consistently staying ahead in the rapidly evolving landscape.I am adept at making significant technical contributions across the entire technology stack, while also focusing on strategic planning and stakeholder relations. My diverse work experience spans implementing machine learning in sectors ranging from governmental projects to creative industries. My strong research foundation is evidenced by my academic work, with publications and presentations at leading conferences such as NeurIPS, IEEE, and EvoSTAR.My experience covers: performing R&D work to tackle specialised large data challenges involving both image & text through machine learning; transitioning research into scalable production models capable of making over a billion inferences; developing data curation pipelines that ensure quality for model training; and strategically directing efforts to stay ahead of competitors, aligned with the latest breakthroughs in the field.
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Dilpreet Singh work experience
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Machine Learning Lead
Lead Machine Learning Engineer
• Stayed ahead in the deep learning field by incorporating cutting-edge research and methodologies into our product offerings. Ensured our company remained a market leader, leveraging our agility and innovation despite having a smaller team and limited resources.• Developed an image search capability, akin to Google Lens, enabling customers to instantly locate similar objects within their datasets, enhancing user experience.• Directed the integration of a large language model (LLM), broadening the scope of the company's ML applications.• Led efforts in computational efficiency, implementing optimisations across the stack to reduce resource consumptionBusiness Outcomes• Achieved significant cost savings and improved service delivery through model and pipeline optimisations, directly contributing to the company’s competitive advantage and financial performance
Senior Machine Learning Engineer
• Pioneered the development and deployment of the company's deep learning infrastructure, comprising 5 specialised ML models.• Analysed millions of high-resolution images, achieving industry-leading false positive rates in anomaly detection.• Developed ETL pipelines for large volume data, resulting in more than 1 billion inferences made with the machine learning models.• Collaborated closely with customers to understand their data analysis needs, facilitating the translation of complex data insights into actionable business strategies• Leading code contributor across stack, utilising PyTorch, Python, and DockerBusiness Outcomes• Enabled the company to secure substantial yearly service revenue through the deep learning suite, setting new benchmarks within the industry.• Surpassed customer expectations in precision and recall metrics, delivering critical analysis to both government and private sector clients.
Machine Learning Consultant
Machine Learning Researcher
Cartographic applications using Machine Learning• Led the design and engineering of a custom U-Net model in collaboration with ETH Zurich toperform Swiss-style relief/terrain shading.• Managed high volume hyper-parameter tuning through Weights & Biases agents.• The team's innovative work was integrated into the recognised Natural Earth dataset, NationalGeographic maps, and resulted in three publications: IEEE 2020, AutoCarto 2022, and NACIS2022.Contributed to the engineering of Eduard, a macOS application for Cartographers, developedby a two-person team, featuring research-driven innovations: http://dilpreet.co/projects/eduardCo-supervised the theses of two Master's students, focusing on Machine Learning applicationsin Cartography.
Research Engineer (Machine Learning)
Led the development of innovative machine learning applications, from healthcare analytics to interactive art platforms. My work, blending research and technical skills, resulted in impactful projects and presentations at prestigious conferences like NeurIPS and EvoStar, contributing to both academic and professional communities.Interactive Augmented Surfaces• Developed an overhead tracking and projection system to transform any surface into an interactive workspace, using a cost-effective and portable design.• Successfully deployed this technology in two major projects: enhancing fluid dynamic simulations for Woodside FutureLab at Monash and creating an engaging Interactive Renewable Energy Table for Monash Tech School.Healthcare and Machine Learning• Led the integration of Machine Learning into the 'Smart Shoe’—a collaborative project withMonash Health and Blundstone.• Developed an iOS app to analyse gait variations using pressure sensor data, implemented withSwift for on-device inference and Python + PyTorch for cloud-based model training.Art and Machine Learning• Created an application for Similarity Search using CNN models; applied this to a scraped andassembled public domain artwork repository (100,000+ artworks).• This concept was expanded into multiple applications, including an iOS app for interactive artexploration, presented at NeurIPS 2018, and a macOS app that merged generative art withsimilarity search, published at EvoStar 2019.
Casual Employee
Casual Website Designer
Colleagues at IP Australia
Other employees you can reach at ipaustralia.gov.au. View company contacts for 906 employees →
Eva De Kool
Colleague at Ip AustraliaCanberra, Australian Capital Territory, Australia
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Kelly Hitchens
Colleague at Ip AustraliaCanberra, Australian Capital Territory, Australia
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Kathy Monaco
Colleague at Ip AustraliaCanberra, Australian Capital Territory, Australia
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Sophie Kusta
Colleague at Ip AustraliaCanberra, Australian Capital Territory, Australia
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Peter Ellis
Colleague at Ip AustraliaCanberra, Australian Capital Territory, Australia
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JH
Jennifer Hutchinson
Colleague at Ip AustraliaCanberra, Australian Capital Territory, Australia
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BK
Blake Knowles
Colleague at Ip AustraliaGreater Brisbane Area, Australia
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Kevin Ryder
Colleague at Ip AustraliaSandringham, Victoria, Australia
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Thanh Tam Chau
Colleague at Ip AustraliaGreater Melbourne Area, Australia
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Zoran Glavinic
Colleague at Ip AustraliaCanberra, Australian Capital Territory, Australia
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Dilpreet Singh education
Honours Degree, Computer Science
Bachelor’S Degree, Computer Science
Education record
Frequently asked questions about Dilpreet Singh
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What company does Dilpreet Singh work for?
Dilpreet Singh works for IP Australia.
What is Dilpreet Singh's role at IP Australia?
Dilpreet Singh is listed as Lead Machine Learning Engineer at IP Australia.
Where is Dilpreet Singh based?
Dilpreet Singh is based in Melbourne, Victoria, Australia while working with IP Australia.
What companies has Dilpreet Singh worked for?
Dilpreet Singh has worked for Ip Australia, Raedyne Systems, Monash University, Sensilab, Monash University, and Ey.
Who are Dilpreet Singh's colleagues at IP Australia?
Dilpreet Singh's colleagues at IP Australia include Eva De Kool, Kelly Hitchens, Kathy Monaco, Sophie Kusta, and Peter Ellis.
How can I contact Dilpreet Singh?
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What schools did Dilpreet Singh attend?
Dilpreet Singh holds Honours Degree, Computer Science from Monash University.
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