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

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

LLM Research Engineer

Responsibilities<ul><li>Research better robot open-loop and closed-loop control system.</li><li>Research ROS relative algorithms and solutions based on multi sensors, such as, Lidar, IMU etc.</li><li>Research OpenCV algorithms and solutions based on single camera and 3D camera sensors.</li><li>Research Generative AI algorithms and solutions based on our robots.</li><li>Research machine learning algorithms and solutions based on our robots.</li></ul> Requirements<ul><li>Degree in Computer Science/ Automation / Electronic / Mechatronic Engineering or related subject</li><li>Experienced in robot kinematics, robot control, robot simulation and Generative AI. Experienced in C/C++/Python, and ROS.</li></ul>

Robotics Engineer

Responsibilities<ul><li>Develop, optimise, and deploy algorithms involving large language models, computer vision, machine learning, and multimodal AI.</li><li>Translate business requirements into data processing, model training, evaluation, inference optimisation, and continuous iteration.</li><li>Explore technical solutions involving RAG, AI agents, model fine-tuning, knowledge bases, and edge-cloud collaboration.</li><li>Work closely with product, software, and hardware teams to transform AI capabilities into stable, scalable product features.</li><li>Track industry and academic advances, and assess technical direction and practical value in the context of business needs.</li></ul>Requirements<ul><li>A master's degree or above from a university ranked among the world's top 100.</li><li>English is the working language; Mandarin Chinese proficiency is required for daily communication and collaboration.</li><li>Proficiency in Python and familiarity with PyTorch, TensorFlow, or other mainstream deep-learning frameworks.</li><li>Solid foundations in machine learning and deep learning, together with relevant project experience in LLMs, NLP, computer vision, speech, multimodal AI, or reinforcement learning.</li><li>Strong engineering implementation, problem-solving, and cross-functional collaboration skills.</li><li>For candidates with exceptional technical achievements, engineering capability, or industry experience, the academic criterion may be flexibly extended to candidates whose relevant subject is ranked among the world's top 100.</li></ul>Preferred qualifications<ul><li>Experience with model deployment, inference acceleration, MLOps, edge AI, or embedded AI.</li><li>Open-source contributions, research publications, competition awards, or experience taking an AI product from zero to one.</li><li>Familiarity with cloud AI services, vector databases, containerisation, and API-based architectures.</li></ul>Compensation and support<ul><li>PhD: first-year base compensation of HKD 700 k to 1,000 k, inclusive of local allowances. There is no upper limit for exceptional candidates.</li><li>Master's degree: first-year base compensation of HKD 400 k to 700 k, inclusive of local allowances.</li><li>A year-end bonus of no less than two additional months' salary.</li><li>An indexed compensation plan, with annual increases no lower than local CPI, together with MPF contributions and employee insurance.</li><li>Access to Hong Kong's major innovation and technology ecosystem, as well as innovation resources and policy support across the Greater Bay Area.</li><li>Assistance with Hong Kong work-visa and residence-status applications for eligible candidates and qualifying dependants.</li><li>A high-quality office environment in Kowloon Tong. For Hong Kong-based roles, single-room talent accommodation with Victoria Harbour views in West Kowloon is subsidised at 50% of market rent.</li></ul>

AI Algorithm Engineer

The Principal Scientist will oversee the process integration from LED wafers and backplanes to final micro-LED display panel/module products.Job responsibilities include<ul><li>Report to the CEO about the micro-LED project update</li><li>Plan and manage all R&amp;D projects</li><li>Upkeep technological development road-map and future trends based on the latest market demands</li><li>Lead a team of researchers to develop, evaluate &amp; characterize micro-LED display product processes and corresponding process tolerances</li><li>Conduct quantitative and qualitative research to improve existing micro-LED process efficiency and yield</li><li>Provide technical support to answer internal/external inquiries</li><li>Review the team’s experimental work, data, and reports to ensure accuracy and compliance</li><li>Provide technical guidance, training, and support to team members Qualifications: </li><li>Ph.D. in Electronic/Electrical Engineering, Mechanical Engineering, or equivalent, with a background in LED/micro-LED active/passive matrix displays (&gt;5 years R and D experience).</li><li>Sound knowledge &amp; working experiences in micro-LED devices/panel processes, including ICP etching, CVD/PVD, sputtering, e-beam evaporation, flip-chip bonding, and packaging processes.</li><li>Knowledge in quantum dot color conversion, and mass transfer technology.</li><li>Familiar with semiconductor mask design software (such as L-Edit).</li><li>Knowledge of micro-lens, projector systems, and colorimetry is a plus.</li><li>Proactive; Good interpersonal and presentation skills in a cross-functional team; high sense of responsibility and good coordination skills</li><li>Excellent command of written and spoken English as well as Mandarin. Able to read &amp; summarize patent/journal publications </li></ul>

Principal Scientist

Position Overview: The Frontend Research Engineer is responsible for designing, developing, and optimizing User Interfaces (UI) and User Experiences (UX) across interactive smart hardware devices, mobile terminals, and cloud-based management platforms. This role focuses on delivering high-performance, low-latency, and privacy-compliant frontend web interfaces that handle complex dynamic data visualization and responsive layout adaptation.Key Responsibilities:<ul><li>Interactive Terminal UI Development:</li><ul><li>Develop responsive frontend user interfaces for multi-screen hardware terminals, self-service kiosks, mobile devices, and desktop web applications.</li><li>Implement adaptive layout frameworks ensuring seamless visual presentation and smooth touch/voice interaction across various screen dimensions.</li></ul><li>Cloud Platform &amp; Dashboard Implementation:</li><ul><li>Build scalable, multi-language (Traditional Chinese, Simplified Chinese, English) web management portals and analytics dashboards.</li><li>Develop modular UI components for dynamic charts, real-time alert logs, custom rule configuration panels, and historical data querying.</li></ul><li>Privacy Compliance &amp; Frontend Data Protocols:</li><ul><li>Implement frontend security standards and privacy-compliant data handling mechanisms.</li><li>Engineer automatic local cache releasing protocols upon transaction or session termination to ensure strict data privacy adherence.</li></ul><li>Frontend Performance Optimization:</li><ul><li>Optimize web assets, DOM rendering, and API fetch mechanisms to minimize page loading times and interaction latency.</li><li>Collaborate with backend and hardware engineers to optimize WebSockets and real-time streaming data rendering for smooth dashboard performance.</li></ul></ul>Core Competencies &amp; Skills:<ul><li>Proficient in modern frontend frameworks (e.g., React, Vue.js, or Angular) and Web UI component libraries.</li><li>Expertise in responsive design, CSS/SASS, JavaScript/TypeScript, and asynchronous API data handling.</li><li>Experience in optimizing web rendering performance, memory management, and implementing data privacy protection protocols. Requirements:· - Bachelor’s degree or above in Computer Science or Software Engineering - Minimum 1–2 years of frontend R&amp;D experience· - Proficiency in React / Vue / TypeScript - Experience in cross-platform UI development and adaptive layouts - Familiarity with Web accessibility or privacy-compliant frontend logic Preferred Qualifications:· - Participation in R&amp;D-oriented projects (not purely commercial outsourcing) - Experience in multilingual interface design - International work experience</li></ul>

Frontend Research Engineer

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.

Where Talent Meets Opportunity