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Company: Universal Tech Limited Location: Hong Kong Science Park (Sha Tin), N.T. | Shenzhen Commuter Friendly : 1-hour direct commute via East Rail Line to University Station + Bus 272K. Employment Type: Full-time Salary Range: HK$16,000 – HK$23,000 / month Application Deadline: 31 August 2026 Contact: universaltech168@gmail.com Languages: Mandarin / English About Us Universal Tech Limited is an innovative technology company incubated at Hong Kong Science Park , specializing in the core R&D of algorithms for home cleaning robots. Adopting a cross-border R&D model between Shenzhen and Hong Kong, we offer a flexible working environment for GBA talents and provide comprehensive support for Hong Kong work visa renewals (IANG / TTPS / QMAS). Research & Development Focus This position belongs to our core R&D initiative: "Full-scene Navigation and Environmental Perception for Home Cleaning Robots." You will focus on solving industry challenges such as localization drift, map relocalization, and obstacle avoidance in complex household environments (e.g., low-light conditions, cluttered layouts, dynamic obstacles). Key Responsibilities (R&D Oriented) 1. SLAM Algorithm Development (Laser / Visual Navigation) Research and develop SLAM algorithms (LiDAR, Visual, and sensor fusion) for home cleaning robots, covering core modules: mapping, localization, loop closure, path planning, auto-docking, and resuming cleaning tasks. Enhance algorithm robustness against household-specific challenges to mitigate issues like map ghosting and pose estimation loss. Port and optimize algorithms on low-power embedded platforms (e.g., Allwinner, Rockchip, Jetson Nano), balancing localization accuracy with CPU/memory constraints. 2. Environmental Perception & Vision Processing Develop algorithms for obstacle detection and recognition using RGB-D cameras, ToF, structured light, and ultrasonic sensors in complex household environments. Construct diverse household datasets (covering various lighting, layouts, and floor materials); design and execute Benchmark tests to validate perception capabilities under extreme conditions (low-light, backlight, fast motion). Implement multi-sensor fusion algorithms (IMU, wheel odometry, visual, LiDAR) to improve localization stability during slippage, climbing thresholds, or external collisions. 3. Mass Production & Technical Documentation Collaborate with hardware teams on sensor calibration and consistency tuning to address mass production variances. Draft high-quality technical documentation, test reports, and patent applications to secure intellectual property rights. Support system integration and production line testing; rapidly troubleshoot and resolve algorithm issues during pilot runs and mass production phases. Requirements Qualifications & Compliance Degree: Master's degree or above in Computer Science, Automation, Robotics, Applied Mathematics, Electronic Engineering, or other STEM-related disciplines. (Bachelor's degree holders must have at least 1 year of relevant R&D experience) Work Rights: Must possess legal right to work in Hong Kong, including: Hong Kong Permanent Resident IANG (Immigration Arrangements for Non-local Graduates) TTPS (Top Talent Pass Scheme) QMAS (Quality Migrant Admission Scheme) Hard Skills Programming: Proficient in C++ and Python with solid knowledge of data structures and algorithms; experienced in Linux development. SLAM Expertise: Deep understanding of mainstream SLAM frameworks (e.g., Cartographer, LOAM, ORB-SLAM, VINS-Fusion ); familiar with LiDAR/Visual Odometry, loop closure detection, and Bundle Adjustment optimization. Tools: Skilled in PCL, OpenCV, Eigen, Sophus ; proficient in ROS/ROS2 (node development, Bag debugging); mastery of Git and CMake . Embedded Awareness: Basic understanding of ARM architecture and embedded Linux workflows; strong awareness of performance optimization. Preferred Experience Proven R&D experience in home cleaning robots or service robots with mass production exposure. Familiarity with deep learning for perception (YOLO, Transformer) and deployment frameworks ( TensorRT, NCNN ). Proficiency in ARM NEON, CUDA optimization, or algorithm acceleration on low-power platforms. Publications in top-tier conferences (CVPR, ICCV, ECCV, ICRA, IROS) is a strong plus. Excellent English technical writing and communication skills. What We Offer Visa Sponsorship: Full support for Hong Kong work visa extensions (IANG / TTPS / QMAS). Strategic Location: 1-hour direct commute from Luohu Port, ideal for talents residing in Shenzhen. Product Impact: Work on core algorithms for consumer products with global market reach. R&D Ecosystem: Access to state-of-the-art laboratories and resources at HK Science Park. Compensation: Competitive salary package (HK$16,000–23,000/month) with Hong Kong's favorable tax regime. How to Apply Please send the following documents to microbubble@126.com : CV/Resume Supporting Materials: Academic papers, project reports, GitHub repositories, or demo videos. Email Subject: Application for Algorithm R&D Engineer (SLAM / Computer Vision) – [Your Name]
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.