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

Key Responsibilities<ol><li>Design, build and maintain end‑to‑end AI data pipelines for construction‑site AI projects, including multi‑modal (RGB + IR) dataset acquisition, pre‑processing, alignment, quality control via clustering methods (KMeans, HDBSCAN), data augmentation and annotation standardisation; improve dataset consistency for facade defect detection, on‑site hazard detection and intelligent tower crane modules.</li><li>Develop, train, tune and benchmark deep‑learning models using PyTorch for construction computer‑vision tasks: object detection (YOLO family), keypoint detection and pose estimation for tower‑crane hook stabilisation and site safety monitoring. Measure recall / precision / accuracy and iterate augmentation strategies and model configurations to lift real‑world performance metrics.</li><li>Support data engineering for the AI‑powered Intelligent Tower Crane System: manage on‑site raw data collection, cleaning and validation for hazard detection and hook‑stabilisation modules; analyse system performance and contribute to accuracy and operational efficiency improvements.</li><li>Implement Retrieval‑Augmented Generation (RAG) pipelines for internal research; integrate multi‑retriever modules (BM25, dense retrievers, ColBERT, E5 / GTE‑Qwen‑Instruct), open‑source LLMs, conduct quantitative evaluation using MAP, NDCG, precision and recall metrics. Explore potential LLM / agent‑AI use cases for construction‑site documentation, incident analysis and technical knowledge retrieval.</li><li>Build NLP solutions such as text tokenisation, feature extraction and supervised text classification; process structured / unstructured text data including project reports, site incident records and technical documentation.</li><li>Perform statistical analysis and exploratory data analysis (EDA) using Python and R; conduct quantitative analysis on construction‑site operational data, safety incident datasets and experimental model outputs.</li><li>Construct and optimise ETL workflows; manage SQL and NoSQL (MongoDB) databases, integrate multi‑source datasets to build AI‑ready data infrastructure for construction‑tech research and decision‑making.</li><li>Collaborate cross‑functionally with research and engineering teams, analyse model error cases from real‑world site data, document experimental workflows, model performance and technical findings; support report generation and data visualisation via Power BI / Matplotlib / Seaborn.</li><li>Keep track of state‑of‑the‑art advances in LLM, agentic AI systems, multimodal deep learning and computer vision; prototype new techniques and adapt them for construction robotics, site safety and intelligent tower‑crane research projects.</li></ol>RequirementsEducation<ul><li>Master’s degree in Data Science &amp; Analytics, Statistics, Computer Science, or related quantitative disciplines; Bachelor’s degree in Statistics or relevant STEM field is required.</li><li>Exposure to multimodal learning, computer vision or applied data analytics for engineering domains is an advantage.</li></ul>Technical Competencies<ul><li>Strong programming skills in Python, PyTorch; practical experience with R, SQL, Git.</li><li>Hands‑on project experience building RAG pipelines, NLP text classification, sentiment analysis, computer vision (YOLO‑based detection &amp; keypoint detection), multimodal deep‑learning frameworks.</li><li>Solid experience in data engineering: multi‑modal dataset building, data cleaning, ETL, dataset QC, database handling (MySQL, PostgreSQL, MongoDB).</li><li>Familiar with statistical methods, exploratory data analysis; hands‑on experience evaluating CV / NLP models with metrics including MAP, NDCG, recall, precision, AUC.</li><li>Working knowledge of visualisation tools: Power BI, Pandas, NumPy, Matplotlib, Seaborn.</li></ul>

Research Assistant(Data Science and Analytics)

Main job duties： ①Lead R&amp;D of AI-driven end-to-end unmanned logistics systems in Hong Kong (warehousing / sorting / transfer / communications integration) ②Optimise AI dynamic scheduling algorithms for HK cross-border logistics ③Integrate local supply chain systems, customise intelligent WMS &amp; unmanned operation control modules with on-site commissioning ④Build digital twin simulation platform for order-peak scenarios ⑤Lead IP filings and industry-academia-research collaboration Minimum entry requirement： - Bachelor's degree in [STEM-related subjects] or related subjects with at least 3 years of working experience; - Master's degree in [STEM-related subjects] or related subjects with at least 1 year of working experience; - Doctoral degree holder in [STEM-related subjects] or related subjects (working experience is not compulsory); - HCAI AI certification is preferred.

Title of job position：Senior R&D Engineer of AI Supply Chain Logistics Unmanned Systems

🔹 学历要求：<ul><li>博士学历；</li><li>有机合成、有机化学、应用化学、精细化工、药物化学、化学工程与工艺等化学相关专业；</li><li>具备扎实的有机化学基础理论与反应机理知识，有独立开展课题研究的经历。</li></ul>🔹 工作经验：<ul><li>博士学历，具备独立开展有机合成研发项目的能力，有完整的合成路线设计、小试开发到工艺优化落地经验；</li><li>优秀应届博士毕业生可投递（公司针对博士可争取博士后入站及出站补贴名额）；</li><li>有博士后经历或精细化工、有机合成相关研发经验者优先。</li></ul>🔹 职位详情（岗位职责）：<ol><li>负责高端有机小分子功能助剂、精细化工添加剂的合成路线设计、小试开发、工艺优化及提纯精制等全流程研发工作，保障实验规范、数据可靠。</li><li>配合团队分子选型成果，完成目标小分子定制合成与结构改性，输出稳定、可落地、可放大的合成工艺方案。</li><li>结合产品应用及量产反馈，迭代优化合成工艺，解决副反应、纯度、收率等技术问题，保障产品批次稳定，优化生产成本。</li><li>整理复盘实验数据，完成工艺总结与技术文档编撰归档，沉淀研发技术经验。</li></ol>🔹 任职要求：<ol><li>专业能力：精通各类常规及高端有机合成反应，能独立完成有机小分子、功能助剂的合成路线设计、小试开发及工艺迭代优化。</li><li>实验技能：熟练掌握萃取、重结晶、精馏、柱层析等提纯精制工艺；熟练操作 HPLC、NMR、GC-MS 等检测设备，可独立完成产物检测、数据分析与结构验证。</li><li>问题解决：具备严谨的科研思维，可精准解决合成过程中纯度、收率、工艺稳定性等核心技术问题，擅长数据复盘与工艺优化。</li><li>文档规范：具备规范的技术文档撰写能力，能高效完成实验记录、工艺报告等研发资料的整理归档。</li><li>加分项：<ul><li>具有博士后研究经历，或发表过高水平 SCI 论文（一作）者优先；</li><li>有精细化工助剂、有机催化剂、功能性精细小分子合成研发经验者优先；</li><li>具备定制化小分子合成、结构改性、工艺放大优化实操经验者优先；</li><li>具备量产或工艺放大经验的博士，可作为研发骨干重点培养。</li></ul></li><li>综合素质：良好的团队协作与沟通能力，工作严谨负责、善于学习创新，可适配港深双基地研发节奏，抗压能力良好，恪守科研诚信与安全意识。</li></ol>🔹 福利待遇：<ul><li>薪酬：极具竞争力的薪资待遇（面议，博士薪资不设上限，优秀者可放宽预算）；</li><li>保障：五险一金、带薪年假、节日福利、年度体检；</li><li>补贴：双基地办公补贴（深港通勤支持）；</li><li>激励：绩效奖金、定期行业技术交流；</li><li>发展：完善的职业晋升体系；</li><li>博士专属：可协助申请博士后入站，争取出站补贴名额，增加额外收入。</li></ul>🔹 应聘方式：请将个人简历及相关科研、项目佐证材料发送至招聘邮箱：📧 jennie.zhou@dynano.com

有机合成研发工程师

Key Responsibilities:<ul data-spread="false"><li>Develop and execute the company’s technology strategy, R&amp;D roadmap and product development plan.</li><li>Lead the research, development and engineering application of innovative pavement materials, recycled asphalt technologies and low-carbon road solutions.</li><li>Transform research outcomes into scalable, market-ready products and technical services through laboratory testing, field trials and performance validation.</li><li>Build and manage the R&amp;D team </li></ul>Requirements:<ul data-spread="false"><li>PhD degree in Road Engineering, Pavement Materials, Civil Engineering, Materials Science or another related field.</li></ul>

Chief Technology Officer (CTO)

Responsibilities<ul><li data-line="0">Carry out validation activities (e.g., SE comparison/clinical investigation, usability testing) and perform statistical data collation &amp; analysis.</li><li data-line="1">Define and execute the project verification test strategy, covering electrical, environment, biocompatibility, algorithm and EMC function etc..</li><li data-line="2">Prepare and routinely update TD doc to ensure compliance.</li><li data-line="3">Coordinate with certified third-party laboratories to verify requirements, and work with regulatory agencies to obtain required certifications.</li></ul>Requirements:<ul><li data-line="0">BS/MS degree in Biostatistics, Public Health, Biomedical Engineering or related field;</li><li data-line="1">Proficiency with statistical software such as SAS, Stata, or R;</li><li data-line="2">Experience with standard product development full-lifecycle processes;</li><li data-line="3">A team player with clear communication and a conscientious, detail-oriented working style, with a willingness to learn and grow;</li><li data-line="4">Knowledge and experience in the following areas is a plus: verification and validation of Class III active medical devices, and/or orthopedic equipment used in hospitals;</li><li data-line="5">At least 2 years of relevant experience.</li></ul>

V&V Engineer

We are hiring an AI Research &amp; Development Engineer to take AI models from research into production. You will reproduce and evaluate algorithms, build inference services, and develop backend systems that run reliably in live environments. Job Responsibilities:- Reproduce, implement and optimise AI algorithms and models; evaluate results with multiple metrics (accuracy, latency, resource use)- Engineer validated models into production inference services and keep them stable and observable- Develop backend services, data interfaces and middleware integrations using Python, Node.js or equivalent- Work with product, operations and research colleagues to integrate prototypes into existing systems, including testing, bug fixes and releases- Write technical documentation and reusable methods for model evaluation, deployment and operations Job Requirements:- Bachelor’s degree or above in Computer Science, Information Security, Software Engineering or a related STEM discipline- Minimum 5 years of relevant experience in backend development and/or AI engineering- Solid hands-on experience in Python, and PyTorch or an equivalent ML framework- Familiar with Node.js, Django or similar backend frameworks, and common databases (e.g. PostgreSQL / MySQL / Redis)- Able to work in Chinese and English- Able to work independently and with cross-functional teams Nice to Have:- Experience deploying models, inference APIs or cloud services- Full-stack collaboration experience (e.g. React)

AI Engineer

Job DescriptionThe primary responsibility of the Post-doctoral Fellow is to investigate and develop innovative solutions, commercializable technologies, and functional prototypes in the field of construction robotics. The role combines cutting-edge academic research with entrepreneurial R&amp;D to drive technology transfer, support start-up incubation, and advance the Center's mission of transforming the construction industry. Additionally, the candidate will support project-based innovative engineering teaching and supervise course-based projects. Responsibilities:<ul><li>Lead end-to-end R&amp;D processes from technical proof-of-concept to functional prototypes and market-ready solutions.</li><li>Actively participate in the entrepreneurial development cycle, including business model validation, technology transfer, and preparing technologies for start-up incubation or commercial spin-offs.</li><li>Collaborate with industry stakeholders, investors, and incubator partners to identify real-world construction challenges and evaluate product-market fit.</li><li>Support IP management, patent filings, and technical documentation required for commercialization and venture creation.</li><li>Supervise course-based projects and conduct hands-on engineering tutorials to foster entrepreneurial and innovative mindsets among students.</li></ul> Requirements:<ul><li>A Ph.D. degree with a strong background in a related engineering discipline (preferably CSE, ECE, MAE, or Robotics).</li><li>Strong problem-definition, problem-solving, and system implementation skills.</li><li>Demonstrated interest or experience in entrepreneurial R&amp;D, commercial technology transfer, product design, or tech start-ups (successful industry or start-up incubation experience is a strong plus).</li><li>Experience or strong interest in innovative engineering teaching and leading hands-on tutorials.</li><li>Excellent written and spoken communication skills in English and Mandarin (and/or Cantonese).</li><li>Ability to work independently, proactively, and collaboratively in a fast-paced, multi-disciplinary environment.</li></ul> 博士後研究員職位概述：博士後研究員的主要職責是在建築機器人領域研究並開發創新解決方案、可商業化技術及功能原型。本職位結合前沿學術研究與創業型研發，以推動技術轉移、支持初創團隊孵化，並推進中心重塑建築業的使命。此外，獲聘者需支持以項目為導向的創新工程教學，並指導課程項目。 主要職責：<ul><li>領導從技術概念驗證到功能原型及市場化解決方案的完整研發流程。</li><li>積極參與創業開發週期，包括商業模式驗證、技術轉移，以及為初創孵化或商業衍生作準備。</li><li>與行業持份者、投資者及孵化夥伴合作，識別真實世界中的建築挑戰並評估產品市場契合度。</li><li>支持知識產權管理、專利申請及商業化與企業創建所需的技術文檔。</li><li>指導課程項目並進行手動實踐教學，培養學生的創業與創新思維。</li></ul> 招聘要求：<ul><li>擁有相關工程學科（偏好 CSE、ECE、MAE 或機器人學等）的博士學位。</li><li>具備極強的問題定義、解決問題及系統實現能力。</li><li>對創業型研發、商業技術轉移、產品設計或科技初創企業展現興趣或經驗（具備成功的行業或初創經驗者優先）。</li><li>具備或對創新工程教學及主持手動實踐教學有濃厚興趣。</li><li>具備優秀的英語及普通話（或粵語）口語與書面溝通能力。</li><li>能夠在快速變化及跨學科的環境中獨立、主動且協作地工作。</li></ul>

Post-doctoral Fellow

Help build the intelligence layer for Asia’s AI infrastructureA-Field Tech Limited is a Hong Kong-based AI and network infrastructure company. NexLLM is a Hong Kong-based AI infrastructure company building a stable and secure regional gateway for developers who need reliable access to leading AI models.Our live platform provides developers with OpenAI-compatible APIs across a growing catalogue of models, including Claude, OpenAI, Gemini, Qwen, and DeepSeek. We are now developing the next layer: intelligent model routing, model evaluation, reliability tooling, and developer infrastructure that helps applications choose and operate the right model for each task.We are looking for a full-time AI R&amp;D Engineering Intern to join our engineering team. This internship is designed for a university student who wants practical experience working on real AI infrastructure, applied research, and software engineering problems.You will work closely with the founder and engineering team on projects that affect a live platform. This is not a purely observational internship or a role limited to administrative tasks. You will be expected to learn quickly, build working prototypes, measure results, and contribute to production improvements with appropriate guidance.Internship details<ul data-tight="true"><li>Role: AI R&amp;D Engineering Intern</li><li>Commitment: Full-time internship</li><li>Location: Hong Kong / flexible hybrid arrangement</li><li>Company: NexLLM</li><li>Team: AI infrastructure, model routing, evaluation, and platform engineering</li><li>Duration: To be agreed based on the university programme and candidate’s availability</li><li>Start date: Flexible, subject to mutual agreement</li></ul>What you may work onYour projects will be selected according to your skills, learning goals, and NexLLM’s current priorities. Possible areas include:<ul data-tight="true"><li>Researching and prototyping model-routing strategies</li><li>Comparing models across quality, cost, latency, availability, and reliability</li><li>Building benchmark datasets and reproducible evaluation tools</li><li>Developing fallback, retry, timeout, caching, and quota-management features</li><li>Investigating provider errors, rate limits, response formats, and performance changes</li><li>Integrating new model providers and standardising their APIs and capabilities</li><li>Building scripts, dashboards, data pipelines, and internal developer tools</li><li>Reviewing relevant papers, technical documentation, and open-source projects</li><li>Turning validated experiments into well-tested product features</li><li>Writing clear technical notes explaining methods, results, limitations, and recommendations</li></ul>The work may involve Python, TypeScript, JavaScript, Go, HTTP APIs, databases, asynchronous systems, cloud services, data analysis, and AI model APIs. You will not be expected to know everything before joining; we care about your ability to learn and make steady, evidence-based progress.What you will learnDuring the internship, you may gain practical experience in:<ul data-tight="true"><li>Building and debugging software used by real developers</li><li>Working with multiple commercial and open-source AI model providers</li><li>Designing experiments and evaluating model behaviour</li><li>Measuring latency, cost, quality, failure rates, and recovery performance</li><li>Building reliable API integrations and distributed services</li><li>Understanding how AI gateways, routing systems, and token usage work</li><li>Translating research ideas into practical engineering decisions</li><li>Communicating technical findings clearly</li><li>Working in an early-stage company where priorities evolve quickly</li></ul>How the internship will workYou will normally work through a complete project cycle:<ol data-tight="true"><li>Understand a technical problem and the user or product context.</li><li>Review existing approaches, documentation, and relevant research.</li><li>Form a hypothesis and define how success will be measured.</li><li>Build a small experiment, prototype, or test harness.</li><li>Analyse the results and identify limitations.</li><li>Discuss the findings with the engineering team.</li><li>Improve the solution and, where appropriate, help move it into production.</li><li>Document what was learned and what should happen next.</li></ol>The level of independence will increase as you become familiar with the platform. We provide direction and review, but you should be comfortable asking questions, investigating problems, and taking ownership of agreed tasks.What we are looking forWe are looking for a university student who is curious, technically capable, and motivated to build real systems.You should have:<ul data-tight="true"><li>Current university enrolment in computer science, software engineering, artificial intelligence, machine learning, data science, mathematics, or a related field</li><li>Strong interest in AI models, software engineering, or developer infrastructure</li><li>Basic programming experience in Python, TypeScript, JavaScript, Go, Java, C++, or a similar language</li><li>Familiarity with APIs, Git, databases, or cloud services, through coursework or personal projects</li><li>Ability to break an unclear problem into smaller steps</li><li>Willingness to test assumptions and measure results rather than rely on guesses</li><li>Care with details, reproducibility, and technical documentation</li><li>Ability to communicate clearly and work collaboratively</li><li>Availability for a full-time internship during the agreed internship period</li></ul>Prior professional experience is not required. Strong coursework, personal projects, research projects, hackathon work, open-source contributions, GitHub repositories, or technical writing are welcome.You do not need prior experience with AI gateways, large language model infrastructure, or distributed systems. We value learning ability and practical curiosity more than a long list of tools.Helpful but not requiredWhat makes someone a strong fitYou may be a strong fit if you:<ul data-tight="true"><li>Like understanding how things work rather than only using them</li><li>Enjoy both reading and building</li><li>Can turn a question into a small experiment</li><li>Are willing to start with an imperfect prototype and improve it</li><li>Care about whether your results are reliable and reproducible</li><li>Take responsibility for finishing work and communicating blockers early</li><li>Want to see your work used in a real product</li><li>Are excited by the fast-moving AI infrastructure landscape in Asia</li></ul>This internship may not be the right fit if you are looking only for a passive learning experience, do not want to write or debug software, or prefer a fixed task list with no ambiguity. Early-stage engineering work requires curiosity, initiative, and a willingness to learn unfamiliar systems.Why join NexLLM<ul data-tight="true"><li>Work on a live AI platform used by developers</li><li>Gain practical experience with multiple leading AI models and providers</li><li>Work directly with the founder and engineering team</li><li>Learn about model routing, evaluation, reliability, APIs, and cloud infrastructure</li><li>Build projects that can become real product capabilities</li><li>Receive feedback and guidance from experienced team members</li><li>Explore the intersection of applied AI research and product engineering</li><li>Help build a regional AI infrastructure capability from Hong Kong</li><li>Potentially be considered for future engineering opportunities based on performance and business needs</li></ul>Compensation and university coordinationThis is a full-time internship. Internship compensation, working arrangement, duration, start date, and any university documentation will be discussed with shortlisted candidates and confirmed before the internship begins. Candidates who need an internship agreement, supervisor information, learning objectives, progress reviews, or other university documentation should mention this when applying.How to applyPlease send the following to info@nexllm.ai:<ul data-tight="true"><li>CV or résumé</li><li>University, degree programme, year of study, and expected graduation date</li><li>Internship availability, including preferred start date and duration</li><li>GitHub, LinkedIn, portfolio, coursework, research, or examples of technical work</li><li>A short note explaining why you are interested in NexLLM and AI infrastructure</li><li>One example of a technical problem, project, or experiment you worked on and what you learned</li></ul>Subject: AI R&amp;D Engineering Intern application — [Your Name]NexLLM welcomes students from diverse backgrounds who are excited to learn, build, and contribute to the next generation of AI infrastructure in Asia.

AI R&D Engineering Intern — AI Infrastructure, Model Routing & Applied Research

Job Responsibilities<ol><li>Market Research<ul><li>Gather and analyze market data, competitor information, and customer feedback.</li><li>Identify market trends and opportunities.</li></ul></li><li>Marketing Campaign Support<ul><li>Assist in planning and executing marketing campaigns across various channels (digital, social media, events, etc.).</li><li>Prepare marketing materials and content.</li></ul></li><li>Customer Engagement<ul><li>Support customer acquisition and retention initiatives.</li><li>Handle customer inquiries and provide product information.</li></ul></li><li>Sales Support<ul><li>Provide sales team with necessary marketing resources and support.</li><li>Track and report on marketing campaign performance.</li></ul></li><li>Brand Promotion<ul><li>Help maintain and enhance the company’s brand image.</li><li>Assist in organizing brand-related activities and events.</li></ul></li></ol>

Where Talent Meets Opportunity