工作內容:
• Designing and maintaining cloud-based data warehouse, including data collection, modeling, and storage.
• Maintaining batch and streaming pipelines, ensuring data quality.
• Developing data APIs based on product requirements and deploying them to Kubernetes using Gitlab CI/CD.
• Understanding user needs and handling data retrieval and dashboard support tasks.
• Continuously learning, optimizing data architectures, and introducing new technologies.
This role might be the one you've been looking for if you are eager to get early access to cutting-edge AI and robotics technologies and be passionate about integrating hardware and software to apply AI in solving real-world challenges!
Join us if you're up for the challenge; also, providing an English CV would be a plus!
#Advanced communication skills in English is a must!
*About the Role:
We are looking for an engineer to build and deploy AI agents that can see and interact with the world through robotics systems. You will be working on everything from setting up hardware to coding intelligent agents for customer demonstrations.
*What You Will Do:
Hardware Setup & Deployment (20-30%)
•Install and configure Nvidia Jetson devices on robots
•Set up vision systems and troubleshoot hardware issues
•Ensure quick deployment for demos and exhibitions
*AI Agent Development (40-50%)
•Build AI agents using Large Language Models (LLMs)
•Work with AI frameworks like LangChain, CrewAI, or Hugging Face
•Connect AI agents to computer vision tools and robot controls
•Use platforms like Nvidia Agent Studio or Autogen for UI development
•Debug and optimize AI pipelines to meet project goals
*Computer Vision (10-20%)
•Work on object detection, image segmentation, or OCR systems
•Train and optimize vision models for robotics applications
•Develop new AI vision tools as needed
*Technical Requirements:
•Programming: Strong Python and PyTorch skills
•AI Frameworks: Experience with at least 1 LLM frameworks (LangChain, CrewAI, Nvidia NanoLLM/Agent Studio, Autogen, n8n, etc.)
•Computer Vision: 2+years experience in CV areas ex. object detection/segmentation
•Edge Computing: Experience with Nvidia Jetson devices
•Optimization: Knowledge of TensorRT, ONNX, or similar inference frameworks
•Development: Git, CI/CD, Linux/Windows environments
*Qualifications:
•Master's degree in Engineering, Computer Science, or related field
•2+ years of hands-on AI/Computer Vision experience
•Strong English communication skills is a must
•Ability to present technical solutions clearly
•Flexible and collaborative team player
若您渴望搶先接觸尖端AI與機器人技術,並希望透過融合硬體與軟體以實現運用AI技術來解決現實世界中會面臨到的問題的話,本職務或許是您正在尋覓的機會!
具體工作內容如下:
部屬與設置硬體設備(20-30%)
1.在機器人上安裝並配置 Nvidia Jetson
2.設置視覺系統並排除硬體設備相關問題
3.展場部屬設置
AI Agent 開發(40-50%)
1.使用大型語言模型(LLMs)構建 AI Agent
2.使用 LangChain、CrewAI 或 Hugging Face 等 AI 框架
3.將 AI Agent 與電腦視覺工具和機器人控制系統連接
4.使用 Nvidia Agent Studio 或 Autogen 等平台開發 UI
5.除錯並優化 AI 處理流程,以達成專案目標
電腦視覺(10-20%)
1.開發物體偵測、影像分割或光學字元辨識(OCR)系統
2.訓練並優化應用於機器人的視覺模型
3.根據需要開發新的 AI 視覺工具
技術要求:
1.程式設計:熟悉Python 和 PyTorch
2.AI 框架:至少熟悉一種 LLM 框架(如 LangChain、CrewAI、Nvidia NanoLLM/Agent Studio、Autogen、n8n 等)
3.電腦視覺:具備 2 年以上物體偵測或影像分割等相關經驗
4.邊緣運算:有使用 Nvidia Jetson 裝置的經驗
5.優化技術:熟悉TensorRT、ONNX 或類似推論框架
6.開發環境:熟悉Git、CI/CD、自如於 Linux/Windows 環境中工作
必要條件:
1.工程、計算機科學或相關領域之碩士學位
2.至少 2 年以上 AI / 電腦視覺實作經驗
3.具備良好的英語溝通能力(請準備英語簡歷)
4.能清楚表達技術解決方案
5.樂於協作的團隊精神
【Job Description】
We are seeking a data scientist to address business challenges and fulfill the needs of the product team through data science and machine learning methodologies. This role involves transforming research outcomes—such as models or metrics derived from specific calculations—into scalable products, while also maintaining and supporting existing products.
【Responsibility】
- Define problems from a data science perspective based on business scenarios and propose actionable solutions derived from analytical results.
- Independently execute assigned development or experimental projects, including model training, feature extraction and transformation (ETL), and general analytical tasks.
- Communicate and explain our research projects to other cross-functional teams, ensuring stakeholders understand our deliverables and insights.
【Must Have】
1. A degree in mathematics, statistics, or a related field.
2. Proven experience in developing machine learning models and bringing them into production.
3. Practical experience in designing product performance evaluation metrics.
4. Familiarity with the design and implementation of A/B testing, with the ability to independently analyze test results.
5.Proficient with tools such as Python, PostgreSQL, BigQuery, and Trino.
6.Excellent communication skills and a collaborative team spirit, capable of working closely with both technical and non-technical teams.
# Nice to Have#
1. Hands-on experience with fundamental technologies including Docker and Kubernetes.
2. Hands-on experience with common scheduling tools like Airflow or Argo Workflow.
More Info>>>https://www.ikala.ai
【Who we are ?】
Hytech是一個年輕、充滿活力的團隊,專注於推動金融科技行業的企業技術轉型,是全球領先的管理技術諮詢公司。創新思維和扁平化的管理,讓團隊成員以公開、透明的方式自在工作,也為全球客戶提供卓越的商業價值服務。
【Why join the team? 】
Hytech 團隊在共事的過程中核心技術會與時俱進,即時討論,並且有良好的溝通管道,扁平化管理,任何問題或意見都可以討論及合作解決。密切的與跨國同事團隊交流。
【About the role - Data Analyst】
As a Data Analyst at Hytech, you will analyze user behavior on financial trading platforms, focusing on app users and their growth journey, including conversion and retention metrics. You will leverage insights from user behavior data to optimize engagement channels—such as push notifications—driving the conversion of registered users into funded, active traders.
(作為 Hytech 的數據分析師,您將負責分析金融交易平台上的用戶行為,專注於應用程式用戶增長過程,包括轉化與留存指標。您將運用數據洞察優化平台渠道,例如透過推播通知,提升用戶參與度,並促使一般用戶轉化為活躍交易者)
【身為團隊的一份子您將負責】
1. Develop, implement, and maintain leading analytical systems to solve complex problems and build simplified frameworks.
(開發、實施並維護領先的分析系統,以解決複雜問題並建立簡化框架)
2. Analyze complex datasets to identify growth trends and opportunities.
(分析複雜數據集,識別增長趨勢與商機)
3. Evaluate organizational methodologies and provide source-to-target mapping and information model specification documents for datasets.
(評估組織方法,提供數據集的來源到目標映射,以及資訊模型規範文件)
4. Create best-practice reports based on data cleansing, analysis, and visualization.
(基於數據清理、分析與可視化,建立最佳實踐報告)
5. Assess the efficiency, issues, and inaccuracies of internal systems, and establish and maintain standard processes for handling, processing, and cleansing data.
(評估內部系統的效率、問題與不準確性,制定並維護數據處理、整理與清理的標準流程)
6. Collaborate directly with management and users to gather requirements, provide status updates, and build strong relationships.
(直接與管理層及內部用戶合作,收集需求、提供狀態更新,並建立穩固的合作關係)
7. Work closely with project/product managers to understand and continuously address their analytical needs, including identifying key metrics and KPIs, and providing actionable insights to relevant decision-makers.
(與專案/產品經理密切合作,了解並持續關注其分析需求,包括識別關鍵指標與 KPI,並向相關決策者提供可行的數據洞察)
8. Proactively analyze data to respond to key stakeholder questions or spontaneous inquiries, focusing on factors driving business performance and investigating and communicating areas for improving efficiency and productivity.
(主動分析數據,回應關鍵問題或突發性需求,關注推動業務績效的因素,並調查與溝通可提升效率與生產力的改進方向)
9. Interpret and analyze data to create and maintain interactive visualizations, integrating various reporting components from multiple data sources.
(解讀與分析數據,建立並維護互動式視覺化報表,整合來自多個數據來源的各類報告元件)
10. Define and implement data acquisition and integration logic, selecting appropriate methodologies and toolsets to ensure optimal scalability and performance within the defined technology stack.
(定義並實施數據獲取與整合邏輯,選擇適當的方法與工具組合,確保解決方案在既定技術架構下達到最佳的可擴展性與效能)