As a Machine Learning Engineer, I specialize in developing scalable machine learning systems and data processing pipelines. I am passionate about advancing the field of machine learning, with a particular interest in Generative AI. Experienced in Python and C++. During my free time, I immerse myself in the latest research from top conferences like CVPR and ICML, staying at the forefront of industry developments.
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Machine Learning EngineerEndava Sep 2022 - PresentGreater Melbourne AreaEndava announced the acquisition of DEK Corporation in 2023. As a Machine Learning Engineer, I provide professional consulting services to Seeing Machines, focusing on Machine Learning Operations (MLOps)- Develop a ML converter to transform ML models from various formats into formats compatible with embedded target processors- Design a ML system (high-performance computing cluster) with Slurm framework to improve automation and repeatability of machine learning training procedures- Design a user interface with pybind11 to allow C++ code to operate seamlessly with Python- Collaborating with Algorithm Scientists and Software Engineers to translate and incorporate research code into technology demonstrators- Implement new processes and tooling to reduce the time required to try out new ideas- Writing clear documentation to support technology demonstrations- Assisting with customer-reported issues when required in order to fix problems or limitations encountered in real-world conditions -
Machine Learning EngineerCurvebeam Ai Oct 2021 - Aug 2022Melbourne, Victoria, AustraliaPreviously known as StraxCorp Pty Ltd, this medical device company develops software to analyze images of bone to aid medical practitioners to diagnose and monitor bone disease. As a Machine Learning Engineer, my tasks involve- Design, build and implement the medical image processing pipeline- Investigate, prototype and evaluate different highly innovative machine learning models and image processing algorithms- Analyse and extract useful features from the large volume of clinical data- Continuously integrate, deploy and monitor for deep learning models in the pipeline (MLOps)- Collaborate with other developers and business owners to consistently deliver high-quality work -
Machine Learning EngineerIdeas At Sea Mar 2021 - Sep 2021Port Melbourne, Victoria, AustraliaPreviously known as Ideas at Sea (IAS), this is a highly specialized company focusing on remote sensing solutions with optical radar. As a Machine Learning Engineer, my tasks involve- Develop an artificial-intelligence and computer-vision solutions for object detection and classification from high-resolution imagery and scalar/vector context information- Computer-code development for x86 and NVIDIA Xavier (ARM) hardware devices- Develop and implement interface control documents and software development kits- Develop tools for data manipulation, processor optimizations, other peripheral scripts, code, and tools to support the primary objective- Designed machine learning pipelines and managed large datasets of high-resolution imagery- Worked across a multidisciplinary team to understand and fulfil all project requirements -
Student Research EngineerMonash University Dec 2019 - Dec 2020Melbourne, Victoria, Australia- Collaborated with Australian Centre for Robotic Vision (ACRV) to develop a Franka-Emika Panda robotic arm to perform a handover activity- Worked on a machine learning model on the robotics vision task to recognize human hands while the robotic arm was grabbing an object from the human- Evaluated performance of ML architecture and wrote technical reports on scientific findings- First paper was published by IEEE Robotics and Automation Letters (RA-L) conference journal in 2020 and it was titled "Object-Independent Human-to-Robot Handovers using Real-Time Robotic Vision" (doi: 10.1109/LRA.2020.3026970)- Second paper was accepted by Active Vision and perception in Human(-Robot) Collaboration (AVHRC 2020) workshop and it was titled "Gesture Recognition for Initiating Human-to-Robot Handovers"- Presented the second paper at AVHRC2020 workshop, held as part of Robot and Human Interactive Communication (RO-MAN) conference -
Lab DemonstratorMonash University Aug 2019 - Nov 2019Melbourne, Victoria, Australia- Provided assistance, e.g. circuit analysis, to engineering students in Engineering Design (ECE3091) unit- Supported approximately 50 students during tutorial sessions -
C++ Software Engineer InternAeste Works (M) Sdn Bhd Dec 2018 - Jun 2019Kuala Lumpur, MalaysiaAeste is a small engineering company committed to creating designs that satisfy specific criteria of elegance in both hardware and software solutions. As a C++ software engineer intern, my task involve- Designed Web APIs, e.g. RESTful APIs- Implemented software design patterns- Integrated different backend servers- Network programming with POCO C++ libraries- Developed a web app to generate a Verilog file from a C++ file- Performed security audit to evaluate information system of small companies- Designed an I/O switch based on Wishbone specification- Designed a dual-port RAM based on Wishbone specification- Analysed digital timing diagrams with GTKWave- Synthesised VHDL with Yosys
Jun Kwan Education Details
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Distinction
Frequently Asked Questions about Jun Kwan
What company does Jun Kwan work for?
Jun Kwan works for Endava
What is Jun Kwan's role at the current company?
Jun Kwan's current role is Machine Learning Engineer at Endava.
What schools did Jun Kwan attend?
Jun Kwan attended Monash University.
Who are Jun Kwan's colleagues?
Jun Kwan's colleagues are Josh Williams, Catalin Paval, Ivana Todoroska, Ana Scarlat, Igor Chistruga, Marko Matijević, Gabriela Neagu.
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