Singapore This is your Service description. Use this space to describe what the service entails, benefits for users and any other important information. Brno, Czechia This is your Service description. Use this space to describe what the service entails, benefits for users and any other important information. Zurich, Switzerland This is your Service description. Use this space to describe what the service entails, benefits for users and any other important information. Grouting robot locations Fabrica boasts a worldwide presence, featuring offices and demo units in key locations across the globe. Our headquarters are located in Delaware, while strategically placed offices in Singapore and Brno, Czechia, cater to customers in those regions. For individuals in the UK and Miami, our demo units provide an immersive experience of our robots in action. No matter where you are, we are dedicated to delivering our cutting-edge robotic technology to you. Headquarters Future locations Demo units

We are hiring across software, hardware, and business operations roles for robotics applied to grouting and the Fabricator reinforcement learning platform. Interns may apply for semester-long internship (credit-bearing), full-time for at least 3 months, or in very exceptional cases, part-time for at least 5 months. Generally, University Interns (including incoming ones) get S$1500 a month in gross salary or S$1755 without CPF for full time work, prorated for part time OR portion in share options. If you qualify for our internship under the SG Innovate summation program, you may receive a stipend of S$3000-S$6000 (checkout our projects on their website for more information) Apply now Grouting Fabricator Join us in shaping the future of robotics Why us Open positions in Czechia (hybrid/remote work possible) Software Engineer for Deep Reinforcement Learning Requirements 1 year of any experience with deep learning in Python Interest in reinforcement learning applied to robotics 3 years of experience in C++ or Python development Nice to have Any further general software development experience in C++ or Python Robotics experience Who are you? A brilliant engineer that likes Python code that spends the minimum amount of time in the interpreter You pride yourself in seeing physical impact, not only higher ads revenue Some experience with deep learning (eg. CV, NLP, general classifiers, entity extraction, etc.) Experience in version control (git - branches, pull requests workflow) Willing to work with Agile development methodology Experience with Continuous Development / Continuous Integration (Github pipelines) What will you do? Developing logic and simulations in Python and Pytorch for Isaac Sim Solve problems and eliminate bottlenecks – GPU and distributed computing Write Isaac Sim plugins for other developers using the Fabricator Integrate pre-trained transformer models, photo scans, or CAD programs Make the project development more effective Help in the deployment to the grouting robots Reinforcement learning engineer Requirements 2 years of applied experience with Deep learning in Python Worked on a deep learning focused project Prior experience with reinforcement learning (work, thesis, personal project) Interest in reinforcement learning applied to robotics Experience in version control (git - branches, pull requests workflow) Willing to work with Agile development methodology Nice to have Any general software development experience in C++ or Python Robotics experience Experience with Continuous Development / Continuous Integration (Github pipelines) Who are you? A brilliant engineer that likes Python code that spends the minimum amount of time in the interpreter You pride yourself in seeing physical impact, not only higher ads revenue Hands on experience with deep learning (eg. CV, NLP, general classifiers, entity extraction, etc. What will you do? Developing RL and logic in Python and Pytorch for Isaac Sim Solve problems and eliminate bottlenecks – GPU and distributed computing Delve into rewards, metrics and environments Improve convergence on all levels Turn CAD models into conceptual designs Implement HW design search papers for the Fabricator | link Reinforcement learning researcher Requirements Previous research experience in Deep learning or reinforcement learning (academic or non academic) Knowledge of the Deep RL landscape 2 years of experience with Deep learning in Python Nice to have Robotics experience Software engineering experience Who are you? A brilliant autonomous researcher in the field of Deep RL You pride yourself in seeing physical impact, not only higher ads revenue What will you do? Developing RL and logic in Python and Pytorch for Isaac Sim Conduct research on state-of-the-art reinforcement learning algorithms and techniques in robotics Develop novel RL methods for custom hardware design and control optimization Implement HW design search papers for the Fabricator | link Collaborate with the engineering team to translate research findings into practical solutions Publish research findings in top-tier conferences and journals, showcasing the company's expertise in the field Stay current with the latest research in reinforcement learning, machine learning, and robotics to drive innovation within the company Work on applied deep reinforcement learning project Tackle open ended hardware design search Aim to push the state of the art Test the RL policies on our physical grouting robots, where we have access to all hardware and software Results will be deployed on Singaporean construction site, so you gain applied RL experience Have a lot of freedom to influence the course of the development Small, learning focused Fabricator team with resources for professional growth The option to get significant stake in the company Many tasks are not automated, because of the cost and uncertainty in building robotic solutions. We aim to move the needle on building robotic solutions by automating the hardware design itself. We are building a platform called Fabricator, which aims to make the design process 100 times faster. The idea is to create robots automatically by defining their tasks and operating environments. Right now, we're working on the first stage with the Early Fabricator. It's a simulation tool that helps decide the basics of robot design like shape, mechanics, sensor placement, and drivetrain selection. This could cut down the early design phase for robotics companies by half a year to a full year. ​ We understand this is a hard and research oriented project. To stay grounded in reality, we are our own reference customer. In under 2 years, we've developed a working and profitable grouting robot whose version 4 was optimized by the proof-of-concept of the Fabricator in late 2022. If you come on board, you'd be working on the Early Fabricator, which is currently under development with the aim to roll out to other companies by 2024. It's a real chance to dig into applied deep reinforcement learning, push the boundaries of hardware design, and see your work in action on real robots that are getting their wheels dirty on construction sites.​ Fabricator TL;DR Hear from our employees Do you want to know what it is like working at a such a dynamic and innovative tech start-up? Hear it from our employees and why they love working for Fabrica Ai! Business/Product Development (Early Expression of Interest) Scheduling and joining meetings with prospective clients, investors, and partners Pitch deck design Accounting and purchasing Scouting for new opportunities, writing proposals for them, and pushing Fabrica AI out there Visiting industry trial sites, giving appropriate feedback to product development team Speaking to industry players, ground workers, understanding the process of tile grouting to help us shape our solution, especially from an operational point of view Connecting manufacturers and our product team to build on and iterate our prototype Contributing to our go-to-market strategy for overseas markets beyond Singapore Open positions in the US Hardware Engineering Intern Your internship would revolve around real-world industry deployments taking us from a TRL of 7 to 9. You may be remunerated with a combination of salary and share options. The following tracks are available, you would probably be doing a couple of them up to your preference, with examples of what has been done by previous interns (plus most of assembly has been done by interns): ​ 1)Mechanical experiments and design Experiments - e.g. designing variations to the grout extruder to allow less waste and better reliability Design - e.g. most of the upcoming v4 robot is being designed by interns with Jakub supervising them ​ ​ 2) Mechanical manufacturing, assembly and testing 3D printing - Slicing prints (often for multi-filament printing), managing and repairing printers (we have Tenlog TL-D3, TL-D5, Ender 3, Prusa i3) Outsourcing manufacturing - specifying cabling, machining etc. to manufacturers Machine tools - making some parts by hand when we need to quickly iterate Assembly - putting in inserts, bolting parts together, waterproofing Testing - testing the robot’s grout extrusion and cleaning, making minor adjustments to make sure everything is running properly and robot produces nice grout lines ​ ​ 3)Electrical experiments and design Design - most of our PCBs have been designed by interns, aiming to minimise free wires in the robot, speed up assembly, allow easy modification where needed. Generally connecting all modules, controlling power, providing a physical user interface… Experiments - e.g. sourcing and testing various motor and driver combinations to pick for our drive system ​ ​ 4) Electrical assembly Outsourcing production of cable assemblies and PCBs Where necessary to make modifications - soldering PCBs, soldering power cables, crimping cables Embedded programming Writing object oriented C++ code Keeping the code clean and maintainable Operations, Business, HR, Manufacturing Intern Your internship would revolve around bringing our robot to market. You may be remunerated with a combination of salary and share options. It is possible to combine this with our technical internships for a more “hybrid” role. This internship requires a reasonable amount of technical understanding/engineering interest. Assisting with the recruitment process, including posting job openings, reviewing resumes, and conducting initial candidate screenings. Coordinating and scheduling interviews with job applicants and hiring managers. Assisting in onboarding new employees, including paperwork and orientation. Maintaining and updating employee records and databases. Assisting with HR-related communications, such as preparing HR documents and announcements. Supporting HR team with various administrative tasks. Assisting in the development and implementation of HR policies and procedures. Conducting research on HR trends and best practices. Scheduling and joining meetings with prospective clients, investors, and partners Accounting and purchasing Scouting for new opportunities, writing proposals for them, and pushing fabrica out there Visiting industry trial sites, giving appropriate feedback to product development team Speaking to industry players, ground workers, understanding the process of tile grouting to help us shape our solution, especially from an operational point of view Connecting manufacturers and our product team to build and iterate on our prototype, creating new avenues for manufacturing at scale, manufacturing for reliability Working with Manufacturers for Design for Manufacturing, reliability, and assembly Hiring and recruitment Website and other marketing/public relations management Any other operational duties Software Engineering Intern Your internship would revolve around real-world industry deployments taking us from a TRL of 7 to 9. You may be remunerated with a combination of salary and share options. The following tracks are available, you would probably be doing a couple of them up to your preference, with examples of what has been done by previous interns (plus most of assembly has been done by interns): ​ ​1) (Software) Create new data generator for object detection (ideal is some experience with Blender/Unreal/Unity) 2) (Deep Learning and Machine Learning): Train, and evaluate our computer vision model fine-tuned on synthetic data on a real-world test set. 3) (Deep Learning engineering): Go through the list of researched libraries, use them to integrate the model into ROS2, and evaluate (compute) performance. Test performance uplift on low-power DL co-processors. 4) (algorithms) Write an algorithm to turn object detection bounding boxes in pixel space to 3D space using known constraints (baseline algo already researched). Turn it into a ROS2 node. 5) Robotics DevOps & Real World Industry Trials (must be in Singapore) Understand the whole project and run our ROS2 stack on real HW. Create reproducible testing methodology and evaluate metrics on the HW. Be in charge of the robots on the construction site. Explore and procure new parts/new materials for robot functionality improvement Electrical Engineer Electrical experiments and design Experiments - e.g. sourcing and testing various motor and driver combinations for our main drive system Design - e.g. designing PCBs to replace a mess of wires and extend the variability and power of the control electronics; PCBs for protecting the AC power supply from back-emf voltage spikes Electrical assembly Soldering PCBs and power cables, crimping cables Arduino programming E.g. Writing code for TMC2209 to reduce power usage of our stepper motors and replace force sensors with smart code Controlling and calibrating the extrusion and cleaning systems Robotics DevOps & Real World Industry Trials Understand the whole project and run our ROS2 stack on real HW Create reproducible testing methodology and evaluate metrics on the HW Be in charge of the robots on the construction site. Explore and procure new parts/new materials for robot functionality improvement Open positions in Singapore Open positions in Czechia (hybrid/remote work possible) Reinforcement learning researcher Conduct research on state-of-the-art reinforcement learning algorithms and techniques in robotics Develop novel RL methods for custom hardware design and control optimization Collaborate with the engineering team to translate research findings into practical solutions Publish research findings in top-tier conferences and journals, showcasing the company's expertise in the field Stay current with the latest research in reinforcement learning, machine learning, and robotics to drive innovation within the company Foster a collaborative research environment by working closely with colleagues and sharing knowledge and expertise Reinforcement learning engineer Develop and implement reinforcement learning algorithms for robotics applications Collaborate with the software and hardware teams to integrate RL solutions with custom hardware designs Optimize and fine-tune the RL models for real-world environments and tasks Maintain and improve existing RL codebase, ensuring high-quality code and documentation Analyze and evaluate the performance of RL models, identifying areas for improvement Stay up-to-date with the latest advancements in RL and robotics to identify and implement cutting-edge techniques Software/ML Engineer Work on ROS2 foxy nodes logic/topics for object detection with the main camera, Floor segmentation, Feedback-loop based navigation correction Auto calibration of cameras, LIDAR (position, noise, hardware characteristics) Advanced procedural Gazebo simulations to automatically evaluate the robots performance on suite of metrics 2D box physics based simulations for Reinforcement Learning (RL), setup and run RL experiments Our ideal candidate A great candidate would possess the following: Willing to work without a very well defined job scope and willing to adapt to changes week on week​ Strong algorithmic thinking Ability to think of metrics to measure progress Understanding of computer science fundamentals, schema design Eagerness to stick to best practices Value the direct impact on the product and proximity to clients at a startup and the growth potential of a startup Growth mindset driven Motivation to build a great product and codebase using the most recent tech stack for the slowly coming robotics revolution Deep learning applied to more than ad revenue, end2end reinforcement learning, etc. Insert other cliche adjectives from other job posts Our development process is very iterative and dynamic. Thus, there would not be a concrete plan more than 2 weeks ahead and your role/tasks is/are likely to evolve over time. If you like this process, you’d be a good fit for us. You would thus play a significant part in deciding how your work would contribute to our overall goals. There are some exceptions to this such as our Gazebo simulation, which has already been verified. ​ If you are applying for an internship, we are looking for a minimum duration of either 3-months full-time or, in very exceptional circumstances, 5-months part time. Internships are open all year-round with rolling closes, generally closing a few months in advance. For example, our summer internships for 2023 are filled around March. ​ ​ Please email your Resume to careers@fabrica.ai with an introduction of yourself, the role(s) you are applying for, and the time period you are applying for if you are interested. Thank you. ​ *If you are interested in the software positions in our Czech office but are based elsewhere, you may still send in your application. Grouting robot

To start building up the fleet, we developed an automatic tile grouting robot This robot boosts productivity 5x Learn more Book demo or Industrial partners Tested at 15 construction projects across Singapore with our clients adding up to 40% of the local market. Want to join us? We are hiring! We are based in US, Asia and Europe. We are looking for brilliant people in business development and mechanical, electrical and software engineering. Full-time, interns and remote. Open vacancies Sounds interesting? We are hiring! Get hired! Mechanical Engineering Electrical Engineering Software/ML Engineering Reinforcement learning Engineering Reinforcement learning Research Creating a future where robot development takes days, not years. Read More Simulation is faster than prototyping We envision a platform that revolutionizes robot development by transforming your environment and task descriptions into custom hardware designs. Our system rapidly generates numerous designs and evaluates each one by fine-tuning the foundation model with reinforcement learning. ​ Custom hardware design minimizes the price and complexity of each robot. Learned optimal control maximizes efficiency. Read More 15 mins of training on a single GPU Learned grouting arbitrary room Building the platform requires a large fleet of robots to learn on We envision a platform that revolutionizes robot development by transforming your environment and task descriptions into custom hardware designs. Our system rapidly generates numerous designs and evaluates each one by fine-tuning the foundation model with reinforcement learning. ​ Custom hardware design minimizes the price and complexity of each robot. Learned optimal control maximizes efficiency. Creating a future where robot development takes days, not years. Read More

Our vision is to revolutionize robotics by eliminating the slow and costly nature of traditional robot development. We aim to create a platform that generates robot designs alongside their optimal control policies, streamlining the process and opening up new possibilities. "I think one could make progress in robotics today. … Build many thousands, tens of thousands, hundreds of thousands of robots and somehow collect data from them and find a gradual path where the robots are doing something slightly more useful." Ilya Sutskever Chief Scientist of OpenAI The time is now Grouting Grout & tile cleaning Tiling HVAC installation Wall grinding Paving Asbestos removal Fireproofing Aquatic weed removal Ship hull cleaning Drywall installation Space mining Cleaning solar panels Roadmap 01. Having taken the initial step by developing our first grouting robot using conventional methods, we now move to the next phase. This involves training a control policy with reinforcement learning in simulation and running it on the Grouting Robot V4, demonstrating the capability for multi-hour task execution. 02. As we progress, we'll identify the next task for which we want to create a robot. Utilizing our platform, we'll generate multiple robot designs for the new task, build and test them in parallel, and ultimately bring one to revenue, showcasing the potential of our groundbreaking approach. ​ Our focus lies in a subset of robotics tasks that do not involve external agents. We'll start with tasks similar to grouting and gradually move to any tasks without external factors, tackling challenges of increasing complexity while refining our platform and expanding its capabilities. 03. Upon reaching a suitable level of development, we'll open the platform to the public, transforming it into the new CAD for robotics innovation. Accelerating the robot design process is achieved by shifting the burden from developing software controls to creating high-fidelity simulations. The term "high-fidelity" holds different meanings for various tasks. For certain tasks, a highly detailed and realistic simulation is essential for accurately assessing robot performance. On the other hand, some tasks might only require basic representations of the environment and interactions. We envision training a foundational model capable of fine-tuning for specific robotics tasks, which would then be used to predict the immediate outcomes of events based on intricate knowledge of the possibilities. Full future distribution. For example, the model could anticipate the effectiveness of grout application, the likelihood of a nail breaking under the robot's force, potential damage to objects upon contact, or the breaking point of aquatic weeds during removal. To ensure the model's predictions closely align with reality, it is crucial to collect data from a large fleet of robots that interact with the diverse, real-world industrial environment, as opposed to being confined to predefined spaces like car manufacturing robots. While companies like Google and Facebook AI have developed unbounded robots, they do not have thousands-strong fleets for large-scale data collection and evaluation. End to end solution was previously unfeasible We will transform the cost of robot development. New industries will emerge as a result. With our system, robots will be developed 100× faster

Automatic grouting robot Using Computer Vision and Robot Operating System (ROS), we designed a compact and precise grouting robot that is fully autonomous. Our robot is able to fill up the grout in all the grout lines in a particular room. It'll be navigating past obstacles such as pipes and drain holes to completely automate the tile grouting process. Human intervention is only needed from room to room due to the steps separating them. The robot does the real-time mapping of the rooms (including irregularly shaped corridors and the main living area) and grout an entire apartment with minimal intervention — ideally in just a start and forget manner. Contact Us In numbers Up to 5x faster grouting Up to 100m2 of grouted area per hour Up to 5 robots operated by a single person 30m2 grouted per hour per robot 5 robots operated by a single person 150m2 grouted per hour per person 5x productivity boost Full name Company Email Demo location Phone Message Submit Thanks for submitting! Contact us for a demo Headquarters Future locations Demo units Small and portable About 20 kg unladen (about 100 hamburgers), less than 50 cm on each side (about a bald eagle) CONQUAS compliance Quality control of the grouting A camera continuously detects uncleaned grout or defects, including on the tiles. Data can be synced with BIM upon request Grout Tile gaps and wash off excess grout autonomously Even in odd-shaped rooms 2+ hours of unsupervised operations Sufficient to cover a standard living room without reload . Under 15 mins set-up time every 2 hours. Operators only needed to reload grout and water. Handles obstacles and keep-out areas Both drawn in seconds on a roughed laptop Single button setup Start and forget Able to climb steps Up to 5 cm Automatic Grout mixing mechanism Further reduce human intervention 1 operator manages more than 10 robots. Allows overnight grouting of a large area. PNG map of the room before/after grouting Useful for progress tracking Coming soon Features Engage us now with no upfront costs Initially, we offer a free trial of our grouting robot, during which it will grout a small designated space, typically a living room. Commercial terms are only finalized once we demonstrate a proven track record and meet your quality standards. ​ After the trial, we operate as a subcontractor, taking full responsibility for the grouting and cleaning process. Payment is made upon satisfactory completion of work, in a few installments per project, and is calculated based on the total length of grout lines. We bear all the risk and responsibility for completing the work, ensuring you get instant savings as we charge less than any local subcontractor, with no cost incurred for any unfinished tasks. ​ As we further optimize our system and make it even more user-friendly, we plan to transition to offering our grouting robot for rental or sale.

Founders Our team members have known each other for years through events like the International Olympiads, hackathons, organizing extracurricular camps, and student society leadership roles. CEO Jakub Suchanek With an engineering degree from the University of Cambridge, Jakub has experience working on self-driving cars at Wayve, machine learning at Granta Innovation and Wacker. He is a worldwide winner of NASA SpaceApps, and also won the national competition for ESA CanSat. He has won bronze medals in International Olympiads in Informatics and Physics and served as the president of the Cambridge University Robotics Society. COO & CFO Keefe Wayne Teo Keefe, a University of Cambridge engineering graduate, served as president of Hackbridge.io, promoting entrepreneurship in tech. With 100+ citations in research journals and four papers, he won multiple awards at Singapore Science and Engineering Fairs and Chemistry Olympiads. Previously an analyst at Entrepreneur First, he also worked in business development at Bright Kids and Gain City. CTO Ronald Luc Ronald earned a degree in Math and Computer Science from Masaryk University, where he was a teaching assistant, and supervised several deep learning theses. With years of industry experience he has developed eight end-to-end machine-learning solutions. He presented at WeAreDevelopers Congress Vienna with over 2000 attendees, won TechFest Munich, one of the EU’s largest hackathons; and represented Czechia at International Informatics Olympiads. At Fabrica, we're proud of our team's dedication to our vision and their belief in our potential to revolutionize the robotics industry. Many of our employees have chosen to invest in our future by accepting a significant portion of their salary in shares or share options. We believe this demonstrates their commitment and passion for our mission. Our team members come from diverse backgrounds, bringing their unique skills and experiences to our company. Their collective expertise spans various aspects of robotics, engineering, and business development, making us well-equipped to tackle the challenges ahead. ​ ​ We have open vacancies! To vacancies Meet the Team Nelson Ng Head of Engineering Operations ​ ​ Ex-Micron Engineer, NUS Mechanical Engineering Multiple Deans' List. Second Major in Innovation & Design Program. Martin Horáček Lead Software Engineer ​ Math and CS degree from Masaryk University. 1 Research journal publication, Multiple Dean's list. Herman Thong Software and Computer Engineer ​ ​ NUS Computer Engineering Graduate, previously Advanced Systems Intern at DSTA. Stuart Tang Project Manager​ NUS Bachelor of Engineering in Mechanical Engineering and Masters of Science in Industrial Systems Engineering. ​ ​ ​ Tomáš Macháček Software Engineer​ ​ Math and CS degree from Masaryk University​. ​ ​ Ho Soon Yee Electrical Engineer SUTD Engineering Product Development, Global Distinguished Scholar. Christophe Berset Head of New Products at Holcim, Christophe holds an MSc in Civil Engineering from ETH Zurich and an MBA. He has experience as a Lead Site Manager at Bouygues Construction and as a Business Development Manager in the global construction material industry, specifically the mortar industry. Christophe co-founded PrefabSite, a sourcing platform for prefabricated construction elements, and is based in Zurich, Switzerland. Matthew Carli Matthew is the Head of Material Operations at ICON Technology, a hyper-growth, venture-backed 3D construction printing startup. He holds an MBA in International Business from St. John's University in Rome, Italy, and previously led global innovation and strategy efforts at Laticrete International, a leading producer of flooring materials. With comprehensive dry mortar industry experience, Matthew is based in Miami, FL, USA. Kai Junge Kai is a PhD candidate at EPFL's CREATE Lab, focusing on robotic manipulation and distributed intelligence. He graduated from Cambridge in 2021, specializing in computer and information engineering. A robotics hobbyist since 2010, Kai has participated in various national and international competitions and events. His expertise includes rapid prototyping, mechatronics design, and control. Advisors Feng Xin Yuan ​ Software Engineering Intern ​ University of Oxford CS and Philosophy Undergraduate Previous Research And Development Intern at GIC and DSTA Christopher Li ​ Electrical Engineering Intern University of Cambridge Engineering Undergraduate Experience in digital electronics and low-level firmware Pang Qiyun ​ Mechanical Engineering Intern University of Cambridge Engineering Undergraduate Janssen Tanuwijaya Mechanical Engineering Intern University of Cambridge Engineering Undergraduate Devon Cheng ​ Mechanical Engineering Intern and Consultant Singapore University of Technology and Design Engineering Product Development Undergraduate Fu Xiongwei ​ Mechanical Engineering Intern ​ Singapore University of Technology and Design Engineering Product Development Undergraduate Hari Subramanian General Engineering Intern ​ NUS High School Graduate Phupha Amornkijja ​ General Engineering Intern ​ University of Cambridge Engineering Undergraduate, Information and Computer Engineering Gao Qianya Electrical Engineering Intern ​ University of Cambridge Engineering Undergraduate, Electrical and Electronics Engineering Emmanuel Oh Software Engineering Intern ​ Singapore Management University Computer Science Undergraduate Goh Meng Wee ​ Hardware Engineering Intern ​ National University Singapore Biomedical Engineering Undergraduate John Wee ​ Hardware Engineering Intern ​ Victoria Junior College Graduate Gabrielle Gianna Tan Business Development Intern ​ Anglo-Chinese School (Independent) Graduate William Damon Shemmeld Hardware Engineering Intern​ ​ Swinburne University of Technology Engineering Undergraduate Chia T-Yan ​ Hardware Engineering/ Business Development Intern Imperial College London Materials with Nuclear Engineering Undergraduate Justin Seow ​ Hardware Engineering Intern ​ Victoria Junior College Graduate Terence Chan Zun Mun Hardware Engineering Intern ​ Nanyang Junior College Graduate Kong Jin Yu Hardware Engineering Intern ​ Hwa Chong Institution Graduate David Goh Zhe Kai​ ​ Software Engineering Intern ​ NUS High School Graduate Chloe Tan Yi Ling​ ​ Hardware Engineering Intern ​ Nanyang Technological University Renaissance Engineering Programme Scholar Jasmine Guo Business Development Intern University of Oxford Philosophy, Politics and Economics Undergraduate Tee Ying Hong ​ Hardware Engineering Intern Nanyang Technological University Mechanical Engineering Undergraduate Teoh Jing Yang ​ Hardware Engineering Intern ​ National University of Singapore Mathematics and Electrical Engineering Double Degree, E Scholar Leong Song Zhu, Owen​ Hardware Engineering Intern ​ National University of Singapore Computing Engineering Undergraduate Goh Wen Xu ​ Business Development Intern Imperial College London Aeronautical Engineering Undergraduate Cho Hyung Jun Hardware Engineering Intern ​ University of Cambridge Engineering Undergraduate Kong Wen Hao Kevin Hardware Engineering Intern ​ National University Singapore Mechanical Engineering Undergraduate Reuben Tan Jian Wei Hardware Engineering Intern ​ Queensland University of Technology Mechanical Engineering Undergraduate Lee Wooseok Hardware Engineering Intern ​ University of Cambridge Engineering Undergraduate Akira Nguyen ​ Hardware Engineering Intern ​ University of Cambridge Engineering Undergraduate Wachakorn Rachanon Hardware Engineering Intern ​ National Technological University Computer Engineering Luke Toh Hardware Engineering Intern ​ National Technological University Mechanical Engineering Jenny Hou ​ Business Analyst & Operations Intern ​ National Technological University Business Analytics Graduate Our Interns