HKSTP announces the launch of the Student Internship Programme (SIP) 2026, which has been open for applications since mid-May 2026.-SIP 2026 is designed to equip students with essential skillsets, industry exposure, and professional networks, supporting their transition into the innovation and technology (I&amp;T) sector upon graduation. The programme also enables companies to engage early with emerging talent and contribute to workforce development.-Eligible HKSTP partner companies can receive funding support to employ qualified student interns, providing students with meaningful, hands-on experience in real-world business environments.-*Please note that funding support is allocated on a&nbsp;first-come, first-served basis.-For further details, please feel free to contact TecONE at 2629 2383 or sip@hkstp.org.

HKSTP Student Internship Programme 2026

Blooming with AI: HKSTP Summer Talent Fest 2026 cum Kick-off Ceremony for "AI for All" Inclusive Programme-Event Details:&nbsp;Date: 14 July 2026 (Tuesday) Time: 10:00 AM &ndash; 1:30 PM&nbsp; (Register at 10:00 AM) Venue: 1/F -2/F, Building 10W, Hong Kong Science Park, Shatin (The Golden Egg)-Event Rundown:&nbsp;10:00 AI+ Tech Showcase (Try the Tech Live - Experience groundbreaking AI straight from HKSTP park companies)11:00 Welcome Remarks &amp; Keynote Address | "AI for All" Inclusive Programme Kick-off11:30 The AI Leadership Forum (Real Strategies - Learn from industry leaders to navigate the dynamic I&amp;T landscape)12:00 Meet &amp; Spark (Unlock Your Next Milestones - Connect with founders and talents in a relaxing setting to land your next gig)-SIGN UP NOWIndustry Leaders, Founders, and Innovators Registration Link: <a href="https://2vx.io/Xci40uc" target="_blank" rel="noopener">https://2vx.io/Xci40uc</a>Students, Interns and Professionals Registration Link: <a href="https://2vx.io/DeGV7ct">https://2vx.io/DeGV7ct</a>

Blooming with AI: HKSTP Summer Talent Fest 2026

HKSTP Global Internship 2026

HYAB Youth Start-up Internship Programme (YSIP)

Talent Foundry

<ul><li>Conduct pioneering research into Data-centric AI methodologies, shifting the focus from model tuning to systematic data quality improvement and feature engineering for robust labelless detection.</li><li>Investigate and implement Domain Adaptation techniques to ensure one AI core can seamlessly migrate across diverse vertical industries with minimal retuning.</li><li>Investigate Active Learning frameworks to iteratively refine models, developing strategies to prioritise high-value data samples for incremental training, thereby reducing reliance on large-scale labelled datasets.</li><li>Research and develop robust data orchestration pipelines and backend architectures to autonomously identify key features within massive datasets, enabling the continuous evolution of the AI core.</li><li>Research and develop autonomous calibration algorithms (Auto-Thresholding) that dynamically adjust system sensitivity based on real-time production variances and statistical normalisation.</li><li>Design and investigate automated data-quality assessment tools and interactive diagnostic dashboards to ensure that raw visual data meets stringent research requirements while providing clear insights to stakeholders.</li><li>Research and develop secure deployment methodologies, including the encapsulation of research findings into encrypted, hardware-locked SDKs to protect the company's intellectual property.</li><li>Investigate self-diagnostic and profiling interfaces within the SDK framework to enable real-time performance monitoring and error tracing within a black box architecture.</li><li>Analyse and manipulate large-scale R&amp;D datasets to extract actionable insights, utilising advanced optimisation techniques to maximise system throughput and consistent alert reliability across varying sensors.</li><li>Optimise research-driven models for heterogeneous computing (NPU/GPU) on the selected AIPC platform, ensuring the scalability and reliability of the data-exchange layers between edge and server.</li></ul>Job Requirements<ul><li>Degree in Computer Science, Data Science, Statistics, Mathematics, or Artificial Intelligence.</li><li>Proficiency in programming languages such as Python and C++, conducting research-to-SDK encapsulation and backend architecture.</li><li>Strong understanding of Domain Adaptation, Transfer Learning, and Domain Generalisation principles to facilitate cross-industry model deployment.</li><li>Experience with backend frameworks and database systems for building scalable, data-driven services.</li><li>Strong understanding of Data-centric AI principles, specifically in the areas of data cleaning, automated labelling, or feature selection for computer vision.</li><li>Experience in developing machine learning models for computer vision, specifically in labelless detection, unsupervised learning, or active learning.</li><li>Familiarity with frontend visualisation libraries to translate research findings into functional internal dashboards.</li><li>Ability to derive scientific conclusions from noisy, large-scale datasets and build scalable software tools to support these findings.</li></ul>

Computer Vision Machine Learning Research Engineer

About UsBLT was founded in July 2011 and officially listed on the STAR Market of the Shanghai Stock Exchange on July 22, 2019. It operates subsidiaries in Hong Kong, Germany and the United States. As a national high-tech enterprise, BLT owns high-level research platforms including the National Enterprise Technology Center. As of the end of December 2025, the company employs 3,531 staff, among whom R&amp;D personnel account for approximately 19.48%. It has filed 738 independent patents related to metal additive manufacturing technology.BLT (Hong Kong) Technology Co., Limited is a wholly-owned subsidiary of Xi’an BLT Additive Manufacturing Co., Ltd. Located in Hong Kong Science Park, it mainly engages in R&amp;D of additive manufacturing and research on cutting-edge application technologies.Job OverviewThis position serves as an AI Researcher for Additive Manufacturing. Its core mission is to systematically identify scenarios in metal 3D printing that can be optimized via AI, develop algorithmic models for metal 3D printing, and lead the R&amp;D of machine learning algorithms integrating physical data and physics-based simulation. Leveraging AI algorithmic models, the role aims to improve printing precision, yield, throughput and equipment scalability, realize industrial applications of AI manufacturing, and continuously strengthen the competitiveness of the company’s 3D printing technologies and solutions.Key Responsibilities<ol><li>Design and develop machine learning models for metal 3D printing workflows, and build hybrid modeling frameworks combining first-principles physical rules and data-driven learning.</li><li>Take charge of designing predictive and closed-loop control learning models for metal printing systems. Based on multi-modal in-situ sensor big data, explore correlations between process parameters, equipment status, part geometry and thermal/mechanical forming quality.</li><li>Develop automated supervised learning algorithms for printing processes, identify quality control points, explore relationships between process signals and part quality &amp; performance, and establish algorithmic control models based on process signals.</li><li>Embed machine learning models into physics-based simulation, digital twin and real-time autonomous closed-loop control systems; develop learning solutions for equipment health monitoring, anomaly detection and fault diagnosis, and deploy them effectively to industrial production scenarios.</li><li>Establish parametric printing algorithm models for diverse metal 3D printing industries and products to realize printing parameter optimization and automation, as well as expand new industrial application scenarios for 3D printing equipment.</li><li>Industrial data and intelligent asset accumulation: Build standardized additive manufacturing process knowledge bases and knowledge graphs based on corporate process documents, experimental data and production cases; collaborate with SLM software and process databases to complete data cleansing and feature sorting, construct automated process development workflows, and accumulate reusable industrial AI application assets.</li></ol>Job RequirementsMandatory Requirements<ol><li>Doctorate or above with over 5 years of applied machine learning research experience, majoring in machine learning, applied mathematics, physics, robotics, control or other related disciplines.</li><li>Solid expertise in machine learning for physical system modeling and control.</li><li>Proficiency in basic programming languages such as Python.</li><li>Strong capabilities in cleansing, analyzing and aggregating complex industrial data, and aligning industrial data pipelines with manufacturing workflows.</li><li>Strong passion and career ambition for empowering manufacturing with AI and intelligent manufacturing, and willingness to devote long-term efforts to industrial AI innovation.</li><li>Possess a valid Hong Kong work visa and capable of using English as a working language.</li></ol>Preferred Qualifications<ol><li>Experience as a Product Manager; able to conduct cross-departmental communication and collaboration with product-oriented thinking, and drive demand collection, analysis, development and deployment of algorithmic models.</li><li>Educational background or practical work experience in materials science or mechanical engineering.</li><li>Experience in autonomous robotics, model predictive control, or reinforcement learning for physical systems.</li></ol>What We Offer<ol><li>A leading research platform for additive manufacturing, with industry-leading full-scenario metal 3D printing solutions covering powder materials, equipment, software applications and printing services.</li><li>Full-industry-chain perspective, internal high-quality resource support, international industrial vision, and an exploratory independent research environment.</li><li>Competitive compensation and benefits packages; salary can be reviewed on a case-by-case basis for outstanding candidates.</li><li>Comprehensive training and learning opportunities to quickly master core industry expertise.</li></ol>

AI  Researcher

JOB RESPONSIBILITIES:<ol><li>Research &amp; Development of Advanced Biomechanical Workflows - Design, implement, and optimize open-source finite element analysis (FEA) workflows for orthopaedic imaging, focusing on integrating patient-specific CT data with biomechanical modelling to simulate bone and implant mechanics. - Perform detailed biomechanical simulations to evaluate mechanical behavior under various physiological conditions, addressing key technological challenges such as automated mesh generation for complex bone geometries, assignment of heterogeneous and anisotropic material properties, and multi-scale modeling of bone-implant interactions. - Validate simulation results against clinical and experimental data, ensuring accuracy and reliability of computational models. - Develop advanced algorithms to enhance simulation accuracy, computational efficiency, and robustness, directly addressing scientific and technical uncertainties inherent in patient-specific biomechanical modelling. - Contribute to the development of standardized, reproducible workflows suitable for broader clinical adoption and translational research. </li><li>Interdisciplinary Collaboration &amp; Scientific Advancement - Collaborate closely with interdisciplinary teams including engineers, clinicians, and software developers to refine algorithms, improve computational efficiency, and ensure compatibility with clinical imaging systems, surgical planning tools, and data management pipelines. - Engage in collaborative discussions with engineering, product, and clinical teams, contributing to project planning, progress tracking, and solution optimization. - Establish and nurture research collaborations with clinical partners and research institutions, particularly with clinical experts and hospitals in mainland China, to understand their research needs in orthopaedics, medical imaging, biomechanics, and simulation, and facilitate the application of our technologies in scientific studies. - Independently conduct clinical scientific research, managing the full cycle of projects from initiation to publication, with a preference for candidates with first author publications in relevant SCI Q1 journals or patents. </li><li>Technical Expertise &amp; Innovation - Leverage understanding of regulatory frameworks (e.g., NMPA, FDA 510(k)) to guide R&amp;D strategies and ensure developed solutions meet regulatory standards for Software as a Medical Device (SaMD). - Provide feedback from R&amp;D activities to product development teams, contributing to product enhancements and new feature development based on scientific findings. - Participate in industry events, conferences, and workshops to stay abreast of emerging technologies and research trends in medical AI and imaging solutions.</li></ol> QUALIFICATIONS:<ol><li>A PhD in Biomedical Engineering from a recognized university, and preferably with a research background in orthopaedics, biomechanics, simulation, or medical imaging.</li><li>Proven experience working in the fields of medical devices, orthopaedics, and medical imaging AI solutions, particularly in the development and validation of computational models, as well as working on finite element analysis (FEA) workflows for orthopaedic imaging and biomechanical modelling. </li><li>Demonstrated ability to independently conduct clinical scientific research, manage projects from initiation to publication, and secure external funding, particularly with clinical clients and research institutions in the mainland Chinese market. </li><li>Strong understanding of AI/ML concepts and their application in orthopaedic biomechanics, advanced medical imaging analysis, and surgical simulation. </li><li>Experience with regulatory processes for medical devices (e.g., NMPA, FDA 510(k), NMPA) and previous experience with on-site submissions and inspections at testing institutes is highly desirable. </li><li>Fluency in Mandarin and English.</li><li>Flexible to accommodate travel requirements.</li></ol> HOW TO APPLY: Interested applicants should send their up-to-date CV and research publication list (where applicable), quoting the job post on the subject line, and include information of current/expected remuneration and availability in the main body, to office@conovamed.com. Review of applications will commence as soon as possible and continue until the post is filled. The personal data provided in your application process will be used for recruitment and other employment-related purposes.

Research and Development (R&D) Engineer

What you'll do:<ul><li>As a Senior AI Engineer in WISIO Tech, you will research, design, develop, and implement AI-powered modules and solutions. These modules include, but are not limited to, event detection, semantic and instance segmentation, and vision large language models (VLM/LLMs).</li><li>Research on industry/academic trends, algorithms and emerging technologies in Edge-Optimized Multimodal VLLM Architecture, Vision AI, machine learning, and computer vision technologies.</li><li>Collaborate with cross-functional teams to gather system requirements and ensure compatibility with existing infrastructure. Optimize and test hardware limit and software components.</li></ul><ul><li>Regularly assess and refine the performance of AI models to identify and resolve any issues or biases.</li><li>Provide technical expertise and support, training users on the AI-powered platform and applications. You'll be a good fit if you have/are:<ul><li>PHD or above degree in Artificial Intelligence, Computer Science, Engineering, Data Science, or a related field</li><li>1-3 years of experience in developing and deploying AI/ML-based solutions, preferably in computer vision domains</li><li>Strong understanding of machine learning algorithms, deep learning, LLM and Computing Infrastructure</li><li>Proficient in programming languages and AI frameworks such as Python, TensorFlow, PyTorch, or similar</li><li>Excellent problem-solving, analytical, and critical-thinking skills</li><li>Excellent verbal and written communication skills in English, Cantonese/Mandrin </li><li>Note that experienced candidate will be invited for higher role</li></ul></li></ul>

Senior AI Engineer

部门：AI智能体研究中心 地点：香港, 深圳 工作经验：实习生、应届生 招聘人数：10人 关于岗位我们正在寻找多智能体协同工程师，加入 echOS Agent Core 团队。你将直接参与设计与实现：<ul><li>多业务 Agent 的角色划分与职责边界</li><li>跨 Agent 状态同步与数据一致性</li><li>Agent 间协商、冲突解决与联合决策机制</li><li>多 Agent 在真实交易系统中的稳定运行</li></ul>这是多智能体系统在真实产业场景中的工程化落地，而不是仿真环境中的理论实验。⸻工作重点（Focus）你将负责构建 echOS 多智能体协同基础设施，包括但不限于：Agent 架构层<ul><li>设计多 Agent 的角色模型（定价 / 库存 / 履约 / 渠道 / 计划）</li><li>构建 Agent 生命周期管理（启动、暂停、恢复、重组）</li><li>定义 Agent 权限边界与职责分离机制</li></ul>协同与决策层<ul><li>实现 Agent 间通信协议与状态广播</li><li>构建冲突检测与协商框架（如价格 vs 库存、时效 vs 成本）</li><li>支持集中式 + 分布式混合决策</li><li>引入多智能体强化学习（MARL）优化整体系统收益</li></ul>系统工程层<ul><li>构建多 Agent 仿真与回放环境</li><li>实现协同行为可观测系统（决策链路、责任归因、效果评估）</li><li>搭建 A/B 框架评估协同策略</li><li>支持新 Agent 快速接入现有系统</li></ul>⸻理想经验<ul><li>有复杂系统 / 分布式系统 / Agent 系统经验</li><li>熟悉 Python</li><li>理解强化学习或博弈论基本概念</li><li>能将复杂业务拆解为多个自治模块</li><li>具备系统级抽象能力</li></ul>加分项：<ul><li>Multi-Agent RL</li><li>博弈论 / 机制设计</li><li>调度系统 / 资源分配系统</li><li>企业级系统架构经验</li></ul>⸻你将面对的真实问题<ul><li>定价 Agent 提高利润但导致库存积压，库存 Agent 要求降价清仓，如何设计可学习的协商机制？</li><li>履约 Agent 为追求交付时效提高物流成本，如何让多个 Agent 自动达成成本与体验平衡？</li><li>新接入一个业务模块（例如促销 Agent），如何快速融入既有协同网络？</li><li>多 Agent 各自局部最优导致整体系统退化，如何设计全局激励？</li><li>企业策略变化（例如从增长导向转向利润导向），如何让 Agent 网络快速重构行为模式？</li></ul>⸻技术栈Python / PyTorch分布式系统多 Agent 框架Typescript / React（内部工具） Department: AI Agent Research Center Location: Hong Kong, Shen Zhen Work Experience: Graduate / Early Career Number of openings: 10 About the RoleWe are seeking Multi-Agent Systems &amp; Coordination Engineers to join our Agent Core team.You will help design and implement systems where multiple autonomous agents: •Share state and communicate •Negotiate resources and objectives •Resolve conflicts •Execute distributed decisions •Form stable long-term cooperation strategiesThis is multi-agent engineering in real industrial environments — not simulated grids.⸻FocusAgent Architecture •Design agent roles (pricing, inventory, fulfillment, channel, planning) •Implement agent lifecycle management (start, pause, recovery, reconfiguration) •Define responsibility boundaries and permissionsCoordination &amp; Decision Layer •Build inter-agent communication protocols •Implement conflict detection and negotiation frameworks •Support hybrid centralized + decentralized decision making •Apply multi-agent reinforcement learning to optimize global outcomes •Enable joint planning across agentsSystems Engineering •Build multi-agent simulation and replay environments •Develop observability tools for coordination behaviors and decision chains •Implement A/B frameworks for evaluating coordination strategies •Enable fast onboarding of new agents into existing ecosystems⸻Ideal Experience •Experience with complex systems, distributed systems, or agent architectures •Strong Python •Understanding of reinforcement learning or game theory fundamentals •Ability to decompose complex domains into autonomous components •Strong system-level abstraction skillsNice to have: •Multi-Agent RL •Game theory / mechanism design •Scheduling or resource allocation systems •Enterprise-scale system architecture⸻Typical Problems You’ll Work On •Pricing agents increase margin but cause inventory buildup — how should agents negotiate? •Fulfillment agents optimize delivery speed at higher cost — how do agents learn balanced strategies? •A new business agent is introduced — how does it integrate into the existing coordination network? •Local agent optimization degrades global performance — how do we design global incentives? •Enterprise strategy shifts (growth → profitability) — how do agents rapidly realign?⸻Tech StackPython / PyTorch Distributed systems Multi-agent frameworks TypeScript / React (internal tools)

多智能体协同工程师（Multi-Agent Systems & Coordination Engineer）

Responsibilities:<ul><li>Software Development</li><li>Firmware Development</li><li>AI Application development using machine learning model</li><li>Algorithm development</li></ul>Requirements:<ul><li> Degree or higher, in Electronic Engineer, Computer Engineering or equivalent disciplines</li><li>We are ready to take in freshmen and grow together with our company</li><li>C++ / C / Python / any related languages</li><li>Able to work independently</li><li>like to work in startup atmosphere</li><li>obsessed in learning and be a better you</li><li>Fluent in Cantonese, mandarin and English</li></ul>

Software Engineer

Job OverviewJoin our team to validate cutting-edge, hyper-realistic Digital Human ecosystems and Agentic AI solutions. In this junior-to-mid-level role, you will perform a blend of manual exploratory testing and internal test automation. Your primary focus will be comprehensive functional software and solution testing—ensuring that all system features, user flows, and application functions work flawlessly alongside our core Speech-to-Text (STT), Text-to-Speech (TTS), and LLM engines across cloud servers, interactive Kiosks, mobile apps, web interfaces, and on-premise hardware.Key Responsibilities<ul><li aria-level="1">Full-Feature Functional Testing: Own the functional testing lifecycle. Thoroughly test all software features, UI components, user navigation buttons, and operational flows to ensure the application behaves exactly as expected.</li><li aria-level="1">End-to-End Solution Testing: Validate the complete software-hardware integration loop. Ensure seamless data flows from physical user inputs on Kiosk/Web interfaces, through cloud-hosted AI layers, and back to the physical display output.</li><li aria-level="1">Validate Audio &amp; Speech Components: Test Speech-to-Text (STT) transcription accuracy and Text-to-Speech (TTS) naturalness, pronunciation, and real-time lip-sync alignment within the live environment.</li><li aria-level="1">Test AI &amp; Interaction Logic: Design and execute test matrices to evaluate LLM conversational branches, chatbot logic, and agentic workflows for multi-language accuracy, context retention, and low latency.</li><li aria-level="1">Build Internal Automation Frameworks: Develop, maintain, and execute automated test scripts targeting cloud APIs, communication pipelines, and core functional software modules to accelerate release cycles.</li><li aria-level="1">Monitor Cloud, Infrastructure &amp; Alerts: Actively watch cloud server metrics and system monitoring dashboards. Triage automated infrastructure or software alerts, investigate log files, and initiate immediate escalation paths for system anomalies.</li><li aria-level="1">Cross-Functional PMO Collaboration: Act as the primary QA anchor working daily with AI, Software, and the PMO teams to track bug resolution lifecycles and ensure software releases hit key milestones.</li></ul>Technical Requirements 🎯 Must Have<ul><li aria-level="1">Experience: 1 to 4 years of proven experience in software testing and complex functional/solution testing (Junior to Mid-Level).</li><li aria-level="1">Functional &amp; Feature Testing Mastery: Strong background in breaking down complex business requirements into detailed manual and automated test cases that cover 100% of application features and user edge cases.</li><li aria-level="1">Solution Testing Frameworks: Demonstrated ability to test multi-tier solutions where software interacts directly with cloud systems, APIs, and physical endpoints (Kiosks/devices).</li><li aria-level="1">Core Languages: Fluency in Python and JavaScript / TypeScript for writing test tooling and validating data.</li><li aria-level="1">API &amp; System Validation: Solid experience with automated API testing tools and functional web/mobile automation frameworks </li><li aria-level="1">Cloud Platform Familiarity: Hands-on experience navigating cloud platforms to verify hosted software components, server logs, and deployment environments.</li><li aria-level="1">Monitoring &amp; Alerting Systems: Direct experience working with telemetry, system monitoring, or cloud logging tools to track software health and react to real-time system alerts.</li><li aria-level="1">Agile Workflows &amp; Collaboration: Active usage of GitHub for version control, along with Jira or similar issue-tracking tools inside structured Agile frameworks. </li><li aria-level="1">Excellent English, Cantonese, Mandarin communication skills (written, reading, and verbal)</li><li aria-level="1">Ability to explain complex technical concepts to both technical and non-technical audiences</li><li aria-level="1">Strong problem-solving and analytical thinking capabilities</li><li aria-level="1">Self-motivated with ability to work independently and drive projects to completion</li><li aria-level="1">Collaborative team player who thrives in fast-paced environments</li></ul>💡 Good to Have<ul><li aria-level="1">AI Ecosystem Knowledge: Conceptual or hands-on exposure to AI Frameworks (LangChain, LlamaIndex), speech processing APIs, or LLM-based applications.</li><li aria-level="1">DevOps Basics: Basic understanding of containerization and deployments (Docker, Kubernetes) to better diagnose environment-specific software issues. Excited to join us? Press APPLY or email your resume to jobs@pantheonlab.ai with - The role you're applying for - Expected salary - Your availability We can’t wait to hear from you! NOTE: All personal data is collected for recruitment purposes only.</li></ul>

QA Engineer (Digital Human & LLM/ Chatbot)

Responsibilities<ul><li data-list="bullet">Manage and execute entire projects or components of data science projects from start to finish including data gathering and manipulation, synthesis and modelling, problem solving, and communication of insights and recommendations.</li><li data-list="bullet">Participate in the design, implementation and interpretation of experiments/trials for continuous refinement of on-going technical proposals.</li><li data-list="bullet">Develop, verify, and validate analytics to address customer needs and opportunities.</li><li data-list="bullet">Translate predictive insights from complex analytical frameworks to optimization.</li><li data-list="bullet">Develop and deploy both traditional statistical models and machine learning techniques and algorithms: Regression, clustering, neural networks, random forest etc.</li><li data-list="bullet">Participate as a Lead, Subject Matter Expert in projects that enable the use of data for analytics across Quest. This requires collaborating with business and technical teams to propose solutions and/or leverage new technologies to address data quality, normalization, and standardization issues.</li></ul>Requirements and skills<ul><li data-list="bullet">Master’s degree (or equivalent experience) or PhD in Computer Science, Artificial Intelligence, or mathematics or related field.</li><li data-list="bullet">Solid understanding of Machine Learning / Deep Learning techniques, algorithms and tools with exposure to CNN, RNN (LSTM), Transformers, know-how of Deep learning applications.</li><li data-list="bullet">Strong development experience in languages like Python, as well as frameworks like Tensorflow, PyTorch, and/or Keras.</li><li data-list="bullet">Familiar with R, Scala, Julia or SAS.</li><li data-list="bullet">Exhibit a passion for AI and data and have a thirst to continually learn and keep pace with the latest innovations and applications</li><li data-list="bullet">Demonstrated skill in critical thinking and problem solving methods</li><li data-list="bullet">Demonstrated skill in presentation and influencing skills</li></ul>

Senior Researcher, AI Algorithm

Software Engineer (Algorithm Deployment &amp; Project Implementation)Job Responsibilities<ul><li>Responsible for on-site software deployment and implementation to ensure stable system operation</li><li>Work closely with algorithm engineers to understand algorithm requirements and implement them effectively</li><li>Perform on-site troubleshooting and debugging, and promptly resolve various technical issues</li><li>Write and maintain relevant technical documentation, recording deployment processes and problem-solving procedures</li><li>Monitor and optimize on-site device performance to ensure stability and reliability</li></ul>Qualifications<ul><li>Bachelor's degree in Computer Science or a related field</li><li>3+ years of software development experience, with proficiency in C, C++, Python, and ROS (Robot Operating System)</li><li>Hands-on experience in on-site software deployment, with the ability to quickly adapt to different environments</li><li>Strong problem-solving skills and the ability to debug efficiently under pressure</li><li>Knowledge of network environments and configurations, with the ability to handle network-related issues</li><li>Good communication skills and the ability to collaborate effectively with algorithm engineers</li></ul>Preferred<ul><li>Valid visa and work authorization</li><li>Proficiency in Cantonese and English</li></ul>

Where Talent Meets Opportunity

Computer Vision Machine Learning Research Engineer

AI Researcher