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

HKSTP Global Internship 2026

HYAB Youth Start-up Internship Programme (YSIP)

“AI for All” Inclusive Programme - Talent Foundry

嚴格按照IPD流程，負責無線連接晶片從概念、計劃、開發、驗證、發布到生命週期管理的全過程。組織各階段的關鍵決策評審（DCP，Decision Check Point），包括概念決策評審、計劃決策評審、可用性決策評審、量產決策評審等，準備高品質的決策評審材料，推動決策高效通過。協調演算法、數位、模擬、軟體、硬體、AE、測試、營運等多團隊，確保各模組按計劃對齊和交付，及時識別和解決跨團隊依賴和介面問題。主動識別項目風險（技術風險、資源風險、進度風險、供應鏈風險），推動團隊提前驗證和規避，對無法規避的風險制定應急預案。配合FAE和AE團隊，跟進重點客戶的項目落地，協調研發資源解決客戶導入過程中的技術阻塞。項目結束後組織復盤，總結經驗和教訓，沉澱為團隊的過程資產，持續優化IPD流程在晶片研發中的落地細節，提升團隊交付效率和一次流片成功率。任職要求 電子工程、通訊工程、微電子等相關專業本科及以上學歷，半導體行業經驗，3年以上晶片研發項目管理經驗。有在IPD體系下成功運作項目的實際經驗，能夠熟練組織DCP決策評審和技術評審（TR），撰寫高品質的決策評審材料。熟悉無線通訊晶片（射頻SOC）的研發流程，理解數位設計、模擬設計、演算法、軟體、驗證、後端等各環節的基本邏輯、關鍵節點和常見風險。對項目交付有極強的owner意識和責任心，適應快節奏、多線程的工作環境，能夠在壓力下保持冷靜和清晰的判斷。

Hong Kong Langting International Limited (香港朗庭國際有限公司) – Hong Kong Science ParkFull-time | Hong Kong (occasional travel to Shenzhen may be required) Job Duties <ul><li> Conduct R&amp;D of AI-driven end-to-end unmanned logistics systems in Hong Kong (warehousing / sorting / transfer / communications integration);</li><li> Optimise AI dynamic scheduling algorithms for HK cross-border logistics;</li><li> Integrate local supply chain systems, customise intelligent WMS &amp; unmanned operation control modules with on-site commissioning;</li><li> Build digital twin simulation platform for order-peak scenarios;</li><li> Participate in IP filings and industry-academia-research collaboration.</li></ul>Minimum Entry Requirements<ul><li> Bachelor's degree in Supply Chain and Logistics, Transport Engineering, Industrial Engineering, Operations Research, Computer Science, Data Science, Information Systems, Automation or related subjects, with at least 3 years of working experience;</li><li> Master's degree in Supply Chain and Logistics, Transport Engineering, Industrial Engineering, Operations Research, Computer Science, Data Science, Information Systems, Automation or related subjects, with at least 1 year of working experience;</li><li> Doctoral degree holder in Supply Chain and Logistics, Transport Engineering, Industrial Engineering, Operations Research, Computer Science, Data Science, Information Systems, Automation or related subjects (working experience is not compulsory);</li><li> HCAI AI certification is preferred. Remuneration HK$35,000 – HK$50,000 per month, with standard fringe benefits (MPF, annual leave and medical insurance) per Hong Kong employment practice. How to apply: Interested parties please send your full resume with expected salary to [HR email].</li></ul>

R&D Engineer of AI Supply Chain Logistics Unmanned Systems

We are seeking highly motivated and talented R&amp;D Optical Engineer to join our company and contribute to the development of next-generation fiber-optic gas analyzers. The successful candidate will lead fundamental research and prototype development on fiber-optic systems based on Raman spectroscopy for trace gas detection. This role is research-intensive and ideal for individuals with strong scientific curiosity, hands-on optical experimentation skills.

R&D Fiber-optic Engineer

RoleDatago turns Chinese and English financial text into structured data products: sentiment scores, named-entity recognition, event classification, used by institutional clients. The team fine-tunes BERT-family encoders on proprietary corpora, maintains rigorous evaluation standards, and builds pipelines around them. As the models are delivered to paying clients, evaluation standards are strict and all results must be auditable.This is a model development role rather than a prompt-engineering position. The work spans training loops, dataset preparation and evaluation design, and the engineer is accountable for the figures the models produce. AI assistants are in the workflow but responsibility for results remains with the engineer.Responsibilities<ol><li>Fine-tune and maintain encoder models (BERT, and more) for classification, NER and sentiment tasks.</li><li>Design evaluation frameworks that reflect client priorities: ranking consistency, correlation against ground truth, and strict point-in-time splits.</li><li>Manage data annotation workflows end to end, including guidelines and quality control.</li><li>Curate large text corpora, covering sampling, cleaning, deduplication and versioning.</li><li>Optimize model serving where required, via ONNX export, quantization and batch inference.</li><li>Maintain experiment records in W&amp;B or an equivalent tool, logging each run's configuration, metrics and artifacts so results can be reproduced and compared.</li><li>Maintain bleeding-edge knowledge in relating areas. </li></ol>Qualifications<ul><li>1-4 years of ML/NLP experience, or a research master's degree with substantive projects, coursework certificates alone are not considered sufficient.</li><li>Hands-on Python and PyTorch proficiency: the candidate should have personally fine-tuned a transformer model and be able to explain the problems encountered and how they were identified.</li><li>The HuggingFace transformers ecosystem, plus fluent pandas/numpy.</li><li>Proficiency with the Linux command line and Git, including running experiments on remote GPUs.</li><li>A critical approach to metrics: an understanding of why accuracy alone can mislead, what data leakage looks like, and why the evaluation split matters.</li><li>Fluent Cantonese, working proficiency in English for documentation and code, ability to process Chinese text in both Traditional and Simplified forms.</li><li>A degree in Computer Science, Mathematics, Statistics, Linguistics or a related discipline, or equivalent demonstrable experience.</li></ul>Preferred Qualifications<ul><li>Finance or fintech domain exposure.</li><li>LLM fine-tuning (LoRA/QLoRA), prompt evaluation, harness-use.</li><li>SQL/ClickHouse.</li></ul>Location of work: Hong Kong Science ParkBenefits<ul><li>Competitive salary</li><li>Annual leave and group medical insurance</li><li>Good team culture</li><li>Assistance to apply for an IANG VISA</li></ul>

NLP & Machine Learning Engineer

主要工作職責：<ol><li>按公司流程要求，及時處理客訴郵件，解答產品、訂單、售後、使用等方面的問題；</li><li>記錄脱敏後的客訴詳情表，同步給總部團隊；</li><li>協助總部團隊排查現網問題，如諮詢客戶故障現象、透過客服系統查詢客戶行為數據脱敏後提供給總部研發團隊等；</li><li>協助總部團隊完成本地產品體驗測試，從歐洲用戶的視角提供產品改進建議。</li></ol>任職要求：<ol><li>香港永久居民，本科以上學歷，具備良好的中英文讀寫及口語能力；</li><li>具備良好的電腦使用技能，熟悉常用辦公軟件（Windows 或 Mac，Office，飛書，瀏覽器等）；</li><li>學習能力強，能快速熟悉產品、流程、工具使用；</li><li>有耐心、責任心強，具備良好的溝通能力。</li></ol>

Customer Service

We are looking for a motivated and hands-on Full-Stack Software Engineer to join our R&amp;D team. This position offers a unique opportunity to gain practical experience in frontend and backend software development within an innovating start-up.Job duties: The candidate will collaborate with our interdisciplinary team to build, maintain, and scale our in-house software applications for collecting, processing, and visualizing water-use data.<ul><li>Frontend Development: Design, build, and maintain web applications for water-use data visualization and internal tools to support IoT fleet management and data analytics.</li><li>Backend Development: Design database schemas, build modular pipelines and services, develop APIs, and optimize system performance.</li><li>Testing and Deployment: Automate testing and release procedures on cloud and on-premises infrastructure.</li></ul>Requirements: <ul><li>Bachelor’s degree or above in Computer Science, Computer Engineering, or a related engineering discipline is preferrable</li><li>1–2 years of solid working experience in software development</li><li>Strong proficiency in TypeScript and experience with modern frontend frameworks (e.g., React, SvelteKit, or Vue.js)</li><li>Proven hands-on experience developing backend applications and APIs using Python (e.g., Django or FastAPI)</li><li>Experience with the following would be an advantage: - SQL databases, key-value databases, and object storage (e.g., SQLite, PostgreSQL, Redis, DynamoDB, S3, etc.) - Containerized deployments and health monitoring tools (e.g., Grafana, Prometheus, or CloudWatch) - Container orchestration and platform infrastructure (e.g., Kubernetes, K3s, or Amazon ECS) - Mobile application development (Android with Kotlin or Flutter) - UX / UI design and wireframing tools (e.g., Figma)</li></ul><ul><li>Self-motivated and strong problem-solving skills</li><li>Able to work independently and with a team</li></ul>Job nature: <ul><li>Location: Hong Kong</li><li>Working days: 5 days per week</li><li>Working hours: 40 hours per week</li><li>Competitive remuneration commensurate with candidate’s background</li></ul>

Full-Stack Software Engineer

We are seeking a Senior Embedded Software Engineer to research, prototype, and develop camera and edge-AI systems for indoor hydroponic growing. This role combines embedded firmware, computer vision, machine learning, cloud/backend development, and hardware/software integration. The engineer will conduct applied R&amp;D, build and deploy AI/CV models, design data pipelines, and help transition prototypes into reliable field-ready systems. They will also document research and support pilot deployments, publications, or patent filings.Duties:<ul><li>Research and prototype camera systems for indoor hydroponic growing operations.</li><li>Conduct applied R&amp;D: literature reviews, experiments, benchmarks, prototypes, field trials, and technical reports.</li><li>Develop firmware for camera/edge devices: image capture, streaming, local inference, OTA updates, sensors, and connectivity.</li><li>Build and train AI/CV models for plant monitoring, growth analysis, or related applications.</li><li>Design backend APIs, cloud services, and data pipelines for device, image, and sensor data.</li><li>Integrate hardware/software with hydroponic systems; ensure security, reliability and performance.</li><li>Write research documentation and support pilot deployments, publications, or patent filings.</li></ul>Requirements:<ul><li>BS/MS in Computer Science, Electronic Engineering, AI, or equivalent experience.</li><li>3+ years of experience building software/hardware products.</li><li>Experience in research projects.</li><li>Experience with embedded systems, cameras, computer vision, and OpenCV.</li><li>Experience with PyTorch or TensorFlow and model deployment.</li><li>Experience with CI/CD, cloud, frontend, and backend deployment.</li><li>Strong programming skills in C/C++, Python, and JavaScript/TypeScript.</li></ul>We offer 5-day work week, bank holiday, annual leave, medical insurance, MPF and result bonus to the right candidate.If you are interested, please send your full resume including available date, existing and expected salary to hr@grow-green.com.

Senior Embedded Software Engineer

We are seeking an exceptionally versatile Application Engineer to spearhead our next generation of extreme‑environment spatial computing products. In this pivotal 0‑to‑1 role, you will bridge the boundaries between underwater AR Head‑Up Display (HUD) optics, hands‑free micro‑interaction (gaze/eye‑tracking), and applied Generative AI infrastructure, transforming professional diving instruments into an intelligent, AI‑augmented spatial wearable ecosystem.This role is responsible for translating extreme physiological and hydrodynamic requirements into rigorous hardware‑software PRDs, leading multi‑modal sensor telemetry integration, directing rapid prototyping (CAD/CNC/Unity), and coordinating cross‑functional teams from early incubation to volume DFM delivery.KEY RESPONSIBILITIES<ol><li data-eleid="14"> Product Architecture &amp; System Definition</li></ol><ul data-eleid="16"><li data-eleid="17">Lead the end‑to‑end product architecture and technical PRD roadmap for underwater AR smart masks (integrating 13ATM/120m structural sealing with ultra‑low‑power optical waveguide micro‑HUDs).</li><li data-eleid="19">Translate extreme hydrodynamic and human‑factor constraints into actionable mechanical, optical, and software engineering specifications.</li><li data-eleid="21">Drive hardware‑software convergence, ensuring seamless synchronization between onboard firmware, microdisplays, and companion mobile platforms.</li></ul><ol><li data-eleid="23"> Spatial UI/UX &amp; Multimodal Interaction</li></ol><ul data-eleid="25"><li data-eleid="26">Architect mission‑critical "hands‑free" interaction paradigms (dual‑channel gaze/eye‑tracking, intentional physiological micro‑triggers, and spatial calibration) for zero‑hand operational safety.</li><li data-eleid="28">Design intuitive spatial UI layouts in AR/XR environments optimized for high‑contrast visibility and minimal cognitive load in extreme lighting conditions.</li><li data-eleid="30">Conduct empirical ergonomic evaluations and statistical interaction modeling to maximize targeting accuracy and minimize false‑trigger rates.</li></ul><ol><li data-eleid="32"> Sensory Telemetry &amp; Autonomous Platform Integration</li></ol><ul data-eleid="34"><li data-eleid="35">Lead multidimensional sensor telemetry fusion (hydrostatic depth, decompression NDL algorithms, gas‑monitoring telemetry, and spatial mapping).</li><li data-eleid="37">Oversee payload integration and environmental data acquisition across wearable displays, companion autonomous mobile platforms, and robotic telemetry systems.</li><li data-eleid="39">Evaluate real‑time spatial positioning, acoustic/optical sensing data, and safety telemetry algorithms to enhance situational awareness.</li></ul><ol><li data-eleid="41"> Generative AI Pipelines &amp; Digital Ecosystem</li></ol><ul data-eleid="43"><li data-eleid="44">Design and deploy production‑level Generative AI workflows (custom Diffusion pipelines, automated feature correction asset libraries) to elevate digital asset generation efficiency.</li><li data-eleid="46">Architect intelligent companion software features, including automated Dive Log synthesis, 3D underwater spatial mapping, and marine biodiversity recognition models.</li><li data-eleid="48">Measure performance ROI, inference latency, and output consistency across cloud and edge AI pipelines.</li></ul><ol><li data-eleid="50"> Rapid Prototyping, DFM &amp; Technical Governance</li></ol><ul data-eleid="52"><li data-eleid="53">Bridge mechanical structural design (SolidWorks/Rhino) with rapid physical prototyping (CNC machining, precision tooling, and hermetic sealing validation).</li><li data-eleid="55">Build real‑time interactive simulation environments in Unity for spatial UX verification and optical calibration prior to tooling.</li><li data-eleid="57">Lead global invention patent drafting across high‑pressure mechanisms, optical alignment, and dual‑channel interaction architectures; contribute to industry safety/ergonomic standards.</li></ul>QUALIFICATIONS &amp; REQUIREMENTS<ul data-eleid="61"><li data-eleid="62">Dual‑Disciplinary Education: Master's degree (or equivalent cross‑disciplinary background) bridging Industrial Design / Ergonomics / Human‑Computer Interaction (HCI) and Mechanical Engineering / Mechatronics from recognized global universities.</li><li data-eleid="65">Advanced Interaction Research Background: Demonstrated research depth in multi‑channel human‑machine interaction systems (specifically gaze/eye‑tracking, intentional ocular triggers, or spatial calibration), evidenced by peer‑reviewed contributions to international journals (e.g., SCI Q1) or tier‑1 conferences (e.g., IEEE/ACM).</li><li data-eleid="68">Physical Computing &amp; Dynamic Platform Experience: Proven track record integrating spatial AR interfaces with dynamic robotic/autonomous platforms (e.g., UAV spatial control, quadruped robotic inspection, or flight telemetry tuning via Betaflight/PX4).</li><li data-eleid="71">Sensory Payloads &amp; Environmental Telemetry: Concrete experience designing or integrating multi‑dimensional environmental sensing payloads (e.g., olfactory/gas concentration, telemetry fusion) for automated spatial data collection and safety analytics.</li><li data-eleid="74">Applied GenAI Infrastructure: Hands‑on experience developing customized Stable Diffusion workflows, neural model fine‑tuning, or structural generative asset correction pipelines delivering tangible commercial returns.</li><li data-eleid="77">Full‑Cycle Incubation to Delivery: Demonstrable experience taking physical hardware products from seed/angel‑backed incubation, competitive user insight discovery, and rapid prototype validation to volume DFM execution.</li><li data-eleid="80">Toolchains &amp; Programming: Proficiency in Unity (XR/AR), Figma, SolidWorks / Rhino / Fusion 360, CNC prototyping workflows, Python (PyTorch/OpenCV), C/C++, and R for statistical modeling.</li></ul>Preferred Advantage (Bonus): Certified in Advanced Technical Diving disciplines (e.g., TDI Advanced Nitrox, Razor Sidemount, or equivalent technical protocols); prior competitive honors in premier robotics championships (e.g., VEX Asian Championship) or elite aero‑modeling competitions.

Staff Product Architect – AI & Underwater AR Spatial Systems

Why join us?<ul><li>Applied research on a genuinely unsolved problem, measured against published baselines rather than demos.</li><li>Build systems that explain themselves. Every decision has to carry its evidence and the rule behind it.</li><li>Learn from an ex-Google applied machine learning engineer and from practising clinicians.</li><li>Your results change how insurers handle real claims.</li></ul>What you'll work on<ul><li>Research how large language models can read a patient record and assign standard medical classification codes by applying the official coding rules, rather than pattern-matching from training data.</li><li>Build retrieval over versioned rulebooks so the system reasons from current guideline text, and measure whether that grounding changes the answer.</li><li>Design evidence-linked outputs, where every code carries the source sentence and the rule that justifies it, and a deterministic checker rejects anything unsupported.</li><li>Build benchmarks and locked holdout sets, and measure accuracy against published machine learning results and human specialist baselines.</li><li>Design escalation logic that flags cases where the evidence or the rule is unclear, instead of guessing.</li><li>Run error analysis with clinical reviewers, and write up methods and results so another engineer can reproduce them.</li></ul>Requirements<ul><li>Bachelor's degree in a science, technology, engineering or mathematics discipline.</li><li>Solid programming ability in Python or TypeScript.</li><li>Working knowledge of machine learning or natural language processing fundamentals, from coursework, research or personal projects.</li><li>Comfort with experiments. You can form a hypothesis, design a measurement, and read the result honestly.</li><li>Patience with detail. Much of this work is careful reading of structured rules and taxonomies.</li><li>Legally permitted to work in Hong Kong.</li></ul>Nice to have<ul><li>Projects or coursework in natural language processing, information retrieval or retrieval-augmented generation.</li><li>Experience evaluating LLM systems, including building test sets and scoring rubrics.</li><li>Exposure to healthcare, clinical or insurance data, or to any formal classification system.</li><li>Reading knowledge of Chinese or another second language.</li></ul>What makes us different<ul><li>A real research question with real data, at a company small enough that your result ships.</li><li>Direct mentoring from the technical founders on experiment design and method, plus clinical review of your outputs.</li><li>Based at Hong Kong Science Park, inside the wider deep-tech community.</li></ul>LocationOn-site at Hong Kong Science Park, Pak Shek Kok, New Territories.Interested?Send your CV and a short note about a technical problem you have investigated to hiring@heynovo.ai

Where Talent Meets Opportunity

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