「Machine Learning Algorithm Development Engineer」的相似工作

We are seeking a highly motivated and experienced Senior Deep Learning Engineer to join our innovative team. In this role, you will contribute to designing, implementing, and optimizing cutting-edge deep learning models for radar applications. Specifically, you will work on advanced deep learning solutions that integrate mmWave radar signal processing with state-of-the-art algorithms. Additionally, you will mentor junior engineers and collaborate with cross-functional teams to drive the boundaries of both Radar sensing and AI technology forward. About KaiKuTek KaiKuTek is a global leader in 3D gesture sensing solutions powered by mmWave radar and embedded AI accelerators. We specialize in key technologies, including Antenna-in-Package (AiP), machine learning algorithms, AI accelerators, and 60 GHz radar transceiver design. Following our recent merger with JMicron Technology Corp., a company founded in 2001 and headquartered in Hsinchu Science Park, we have expanded our product portfolio to include high-speed SerDes bridge controller SoCs for storage applications utilizing USB, PCIe, and SATA technologies. Our innovative sensing technology redefines the human-machine interface, combining mmWave radar with high-speed SerDes to unlock new possibilities and application frontiers. Key Responsibilities • Design, develop, and deploy deep learning models for advanced radar applications, requiring computer vision and digital signal processing expertise. • Optimize and fine-tune models for performance, robustness, and deployment on edge or embedding devices. • Collaborate with data scientists, software engineers, and validation teams to understand requirements and deliver high-quality solutions. • Build and maintain tools and pipelines for data preprocessing, model training, evaluation, and deployment. • Stay updated on the latest trends and advancements in AI and deep learning technologies. • Write clear, efficient code following the best software engineering and machine learning practices. • Mentor and guide junior engineers to foster technical growth within the team. Qualifications • Required: o Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. o 2+ years of experience in deep learning and AI model development. o Strong proficiency in PyTorch deep learning framework. o Proficiency in Python and relevant machine learning libraries. o Strong understanding of neural network architectures, training techniques, and optimization algorithms. o Strong problem-solving skills and the ability to work on challenging technical problems. o Excellent communication and collaboration skills. • Preferred: o Experience with deploying deep learning models on production systems. o Familiarity with model quantization, pruning, and optimization for edge devices. o Knowledge of MLOps tools (e.g., MLflow, Kubernetes, Docker) for model lifecycle management.

維曙智能為創新AI應用開發商，具有全球市場商業化能力。公司有完整的創新孵化管線，包含從想法到技術與市場開發的完整配套流程，讓您將知識落實在各種實際場域中。如果您對以創新解決現實世界問題充滿熱忱，希望了解AI在產業的實務運作以及現實應用有興趣，這裡會是您大展身手的地方。歡迎加入我們。 我們正在尋找一位具備影像處理與深度學習專業的資深 AI / 機器學習工程師，能夠獨立主導模型開發、效能優化與落地實作。此職位需具備優秀的深度學習框架掌握能力，能夠根據資料與任務需求進行模型選擇、訓練流程設計與超參數調整，並具備 AI 產品開發的思維。 【工作內容】 領域：機器視覺 • 負責影像領域 AI 模型的研究、設計與訓練（例如：分類、分割、生成、超解析等任務） • 根據問題需求設計模型架構（CNN / Transformer / diffusion-based models）並進行效能調整 • 透過3D/2D圖學轉換進行多模態資料前處理 • 以深度學習方法, 轉換多模態資料為結構化時間序列資料, 如分類, 辨識, 與異常偵測 • 撰寫可重用模組與封裝良好的 Python 套件，提升團隊研發效率 • 與產品及前後端工程師協作，將模型部署至產品系統或 API • 持續追蹤最新論文與技術趨勢，進行技術導入與內部分享 • 協助 junior 工程師成長並共同解決技術挑戰 • 能針對市場需求提案，論述創新解決方案 維曙機器視覺產品服務請參閱: https://www.vizuro.com/corvus

1. Actively clean, process, and validate Data streams for ML model consumption. Contribute to the implementation of MLOps best practices (CI/CD) and risk mitigation strategies as guided by the engineering team. 2. Actively develop and implement Python scripts and small utilities for model features and basic algorithm testing. Ensure development practices align with model fairness and ethical guidelines. 3. Establish and track technical Key Performance Indicators (KPIs) to measure model effectiveness post-deployment. Document and report potential technical risks identified during implementation. 4. Create and maintain a single source of truth for all active Carrier/vendor technical requirements and specifications. Support the definition of project scope, timelines, and milestones. 5. Act as the central liaison between Engineers, Data Scientists, and Business stakeholders. Translate incoming high-level partner requests into clear, detailed, and actionable engineering specifications and tickets. 6. Provide regular, concise updates for stakeholders on project progress, key metrics, and any blockers. 7. Annual salary: 1000K NTD and above 8. Onsite Google Xindian Office

維曙智能為創新AI應用開發商，具有全球市場商業化能力。公司有完整的創新孵化管線，包含從想法到技術與市場開發的完整配套流程，讓您將知識落實在各種實際場域中。如果您對以創新解決現實世界問題充滿熱忱，希望了解AI在產業的實務運作以及現實應用有興趣，這裡會是您大展身手的地方。歡迎加入我們。 您將成為我們 AI 解決方案研發的核心成員。作為數位雙生AI工程師，您將負責在 Sim2Real 平台（如 NVIDIA Isaac Sim、ROS/Gazebo）上測試並驗證 AI 模型與機器手臂系統的整合，並將模擬中成功運行的控制程式部署至實體機台。和不同團隊合作(AI團隊，硬體團隊)優化與測試模型與控制演算法，完成跨部門專案整合與系統調校。 【主要工作內容】 • 使用 NVIDIA Omniverse 平台進行機器手臂建模、運動規劃（正/逆向運動學、避障與優化）及控制程式開發 • 建置與優化模擬環境與數位孿生場景，確保模擬與實體機台行為一致 • 與AI研發團隊合作，將機器手臂模擬系統與公司 SDG（Synthetic Data Generation） 技術串接，用於資料生成與 AI 模型訓練 • 撰寫、維護與優化控制演算法及相關模組，提升系統穩定性與效能 • 與硬體團隊協作，將模擬成果部署至實體機台並進行驗證 • 參與跨部門專案，支持產品研發與驗證流程的自動化。 維曙機器視覺產品服務請參閱: https://www.vizuro.com/corvus

工作內容： 1. 將AI ISP 影像處理模型部署至車用控制器平台（如 Qualcomm、NVIDIA、黑芝麻、MTK及各家NPU 等），確保AI模型在各類平台穩定運行。 2. 依據產品需求，評估模型在 GPU、CPU、NPU 等運算單元上的算力需求與資源佔用，進行性能分析與優化。 3. 與 AI ISP 演算法開發人員合作，完成模型移植、壓縮、加速與平台適配。 4. 針對不同平台環境進行測試與調優，確保模型滿足車用場景的即時性、穩定性與可靠性要求。 5. 參與車載系統軟硬體整合，協助解決模型部署過程中的技術問題。 6. 持續關注車用 AI SoC、NPU 與 ISP 平台的最新技術動態，熟悉各家平台與NPU使用方式，並提出相關改善與升級建議。 技能描述： 1. 資訊工程、電機電子工程、光電工程、影像處理等相關專業碩士及以上學歷。 2. 5年以上AI 模型開發或平台部署經驗。 3. 熟悉深度學習模型部署流程，具備 TensorRT、ONNX Runtime、TVM 或類似工具的經驗。 4. 具備 C/C++、Python 程式開發能力，了解嵌入式 Linux 環境。 Responsibilities: 1. Deploy AI ISP models onto automotive computing platforms (e.g., Qualcomm, NVIDIA, Black Sesame, MTK and NPU-based platforms), ensuring stable runtime performance. 2. Evaluate computational requirements and system resource usage (GPU, CPU, NPU, etc.) based on product needs, and perform resource consumption and performance optimization. 3. Collaborate with AI ISP algorithm developers to handle model porting, compression, acceleration, and platform adaptation. 4. Conduct testing and fine-tuning across different automotive platforms to guarantee real-time, stability, and reliability standards. 5. Support software-hardware integration for automotive systems and troubleshoot deployment-related technical issues. 6. Stay updated with the latest automotive AI SoC, NPU, and ISP platform technologies, providing insights for improvements and upgrades. Skills Qualification and Experience: 1. Master's degree or above in Computer Science, Electrical/Electronic Engineering, Optoelectronics, Image Processing, or related fields. 2. Minimum of 5 years of experience in AI model development or platform deployment. 3. Familiar with deep learning model deployment workflows, with hands-on experience in tools such as TensorRT, ONNX Runtime, TVM, or similar frameworks. 4. 4Proficient in C/C++ and Python programming, with a solid understanding of embedded Linux environments.

1. Develop industry-oriented software for semiconductor manufacturing. 2. Build up an AI/ML software solution. 3. Optimize software runtime. 4. Build a software pipeline on the GPU cluster. 5. Robust model training pipelines. 6. 1+ years working in software development related to ML / AI will be better. 7. Strong written and oral communication skills. 8. Strong programming skills and ability to debug ML systems. 9. Location will be Taipei City. 10. Lasertec company competitiveness : 公司薪資半導體業界前5%強，為高速成長期公司，升遷管道暢通 。 11. 特休規定優於勞基法、健檢補助、年節獎金、穩定年度分紅調薪...等等。

About TXOne Networks TXOne Networks provides cybersecurity solutions for ICS and OT environments using the OT zero trust methodology. We collaborate with top manufacturers and infrastructure operators to develop practical defense strategies that eliminate security vulnerabilities in industrial settings. TXOne ensures the availability of industrial systems by mitigating cybersecurity challenges that can disrupt operations. Our solutions empower customers to benefit from networked control systems while maintaining operational resilience, personnel safety, and asset security. TXOne Networks is honored to be named again as one of the 10 Coolest IoT Security Companies by CRN in Mar 2025. Job Summary As a TXOne AI Engineer in AI team, you will be part of a high performance team that focuses on ICS and OT Cybersecurity solutions. We are seeking a highly skilled AI Engineer to work with product/security team in developing advanced AI-driven security solutions. The ideal candidate will bring a deep understanding of machine learning (ML), deep learning (DL), and Generative AI (GenAI) concepts, with a strong ability to implement practical applications. This role involves designing and implementing models that can process and analyze data derived from various sources, including files and network packets. The successful candidate will possess strong hands-on coding skills, proficiency in AI frameworks such as TensorFlow or PyTorch, and experience in transforming raw data into actionable model inputs for predictions and inference. Key Responsibilities Your role may be in one or more of these areas: • Research and select the most suitable machine learning or deep learning models based on use-case requirements, data patterns, and performance needs. • Develop and deploy AI/ML models tailored for security applications, ensuring they can accurately interpret and process data from diverse sources such as files and network packets. • Design and optimize preprocessing pipelines to transform raw data into high-quality input for AI models. • Collaborate with security experts to understand data patterns, threat vectors, and operational requirements, applying this understanding to enhance model design. • Develop tools to visualize, test, and validate AI model performance and ensure they meet security industry standards. • Collaborate with the engineering team to integrate AI models into security products, ensuring reliable performance and scalability. • Stay up-to-date with the latest advancements in AI, ML, and security technologies, recommending improvements to maintain a competitive edge. Why TXOne Networks? - Shape the Future: Be part of a team that’s at the forefront of Networking Security technology. - Collaborative Environment: Work with dynamic and talented professionals who are passionate about innovation. - Impactful Role: Play a critical role in driving the success of our groundbreaking products. Ready to make your mark in Networking Security? Join TXOne Networks and be a catalyst for the future of connectivity! Equal Opportunities Statement At TXOne Networks, we embrace change, empower people, and encourage innovation in a connected world. Our diversity and multicultural workforce are key contributing factors to our success across the globe. We like to have fun while taking our culture seriously. We are an equal opportunity employer and are committed to this regardless of race, colour, religion, sex, nationality, age, citizenship, sexual orientation, marital status, gender identity or veteran status. We do not allow discrimination or harassment of any kind.

工作內容 1. 規劃並執行AI應用開發、數據分析。 2. 配合部門主管工作調度、分配。 技能要求： 1. 具備程式語言(Python/R/Javascript/C#/C++/Java等等...)開發/運維能力。 2. 熟悉以下其中一種技能 - AI影像: 深度學習, computer vision, opencv, pytorch, tensorflow - AI知識: LLM大模型, NLP, RAG, Langchain, 向量資料庫, 知識圖譜 - AI數據: 機器學習, scikit-learn, pytorch, tensorflow - 數據分析: 統計分析, 實驗設計DOE, 6sigma黑帶 3.願意學習新技術。 4.有較強的上進心、執行力、溝通能力、創新能力。 5.有智慧製造相關經驗者佳。 6.歡迎應屆畢業、學習意願強想跨領域的人才。 **該缺會長期出差海外地區，有興趣者可直接來電&來信詢問**

【產品說明】 產品為公司自主研發電信產業的行動智慧平台，橫跨多種無限通訊技術，處理海量電信數據並進一步提供深度解決方案。 【職缺說明】 現有開發團隊擴編，尋找具備專業素養的資料分析自動化工程師。 【職務需求】 - 設計分析項目 - 撰寫分析報告 - 分析/測試自動化 - 維護現有自動化分析/測試項目 【技能需求】 - 具備CICD使用經驗 - 使用過Docker/Container - 了解Git操作 - 熟悉SQL, shell script, linux, 以及 python 【技能需求++】 - 無線通訊網路知識/訊令交換資料分析

1. Actively clean, process, and validate Data streams for ML model consumption. Contribute to the implementation of MLOps best practices (CI/CD) and risk mitigation strategies as guided by the engineering team. 2. Actively develop and implement Python scripts and small utilities for model features and basic algorithm testing. Ensure development practices align with model fairness and ethical guidelines. 3. Establish and track technical Key Performance Indicators (KPIs) to measure model effectiveness post-deployment. Document and report potential technical risks identified during implementation. 4. Create and maintain a single source of truth for all active Carrier/vendor technical requirements and specifications. Support the definition of project scope, timelines, and milestones. 5. Act as the central liaison between Engineers, Data Scientists, and Business stakeholders. Translate incoming high-level partner requests into clear, detailed, and actionable engineering specifications and tickets. 6. Provide regular, concise updates for stakeholders on project progress, key metrics, and any blockers. 7. Annual salary: 1000K NTD and above 8. Onsite Google Banqiao Office

【工作內容】 - 設計、實作及優化 DSP 系統中的 ML 模型，包含但不限於 CTR、CVR 預測、出價策略、受眾預測、商品推薦等。 - 分析海量廣告與用戶行為資料，發掘可改善模型與策略的特徵與規則。 - 協作開發 RTB Server 的即時模型推論功能，確保低延遲、高效能。 - 與數據團隊、平台團隊緊密合作，持續改進模型部署與效果追蹤。 - 研究並應用最新 ML 技術於廣告優化與投放效果提升。 【必備條件】 - 熟悉 ML 相關知識 - 完成過任一 ML 相關 project - 熟悉任一程式語言，例如：C# / python / Java / Git 【加分條件】 - 熟悉任一 open source ML 工具，如 tensorflow, pytorch - 曾參與 ML 相關研究、競賽或發表論文 - 曾參與 open source 專案開發 - 有廣告投放、推薦系統或搜索系統經驗 - 有 A/B Testing、效果評估與 KPI 指標優化經驗 - 熟悉 DevOps / MLOps - 熟悉 Testing - 熟悉 Spark 【待遇】 年薪 100 - 130 萬之間，另含認股權證若干。

擔負以下至少一項演算法開發主責： 1.基於事件相機(event camera)與動態視覺感測器(Dynamic Vision Sensor, DVS)相關 (1)設計開發視訊插幀(video frame interpolation)與視訊超分(video super-resolution)以達成慢動作特效與解析度提升效果。 (2)設計開發低照度下動態場景的影像與事件多幀合成，達成亮度提升、移動物清晰、且雜訊抑制效果。 (3)設計開發適用於事件相機的ISP流程，包含自動曝光(Auto Exposure, AE)、去雜訊(降噪)、細節增強等。 2.AI影像視覺邊緣運算 (1)設計目標檢測、識別、分割的輕量化AI模型演算法。 (2)將神經網路模型進行壓縮並移植部署到MCU平台上。 (3)在算力與記憶體(內存)受限的邊緣裝置上實現AI影像視覺演算法。 3.與3D/ToF相關 (1)深度圖修補、去雜訊等後處理。 (2)深度圖應用相關演算法開發，例如先進駕駛輔助系統(ADAS)、同步定位與地圖構建(SLAM)、時空場景重建(Spatio-temporal scene reconstruction )。 (3)結合RGB色彩、事件資訊改善深度圖或輔助前述各項應用效果。 4.軟體演算法硬體化 (1)將現有AE、AF等軟體演算法實現於FPGA上。 (2)ISP相關演算法實現於硬體架構上。

[Job Title]: Data Scientist - LLM(Large Language Model) Applications [About Us]: Founded by ex-googlers and started at Stanford’s StartX program, PowerArena now has offices in the States, Taiwan, Hong Kong and China. We are a fast-growing, research-driven company building AI solutions that helps manufacturing corporations and factories assembly operations overcome the challenges they face in productions every day. We are a fast-growing, research-driven company building AI solutions that helps corporate and factories overcome the challenges they face every day. Using novel machine learning techniques, we are revolutionizing the industry and have a track record of building things that others have ruled out as impossible. Our team is our best asset. We work with smart and talented individuals, who all enjoy a high degree of responsibility and independence in structuring their work. The team are looking for passionate data scientist who is keen to work with like-minded individuals in a rapidly evolving environment. =====[Job Description]===== [Position Overview]: We are looking for a Data Scientist specializing in LLM to drive our LLM appliactions. As a Data Scientist at PowerArena, you will work on projects about smart factory and smart city, and tackle a diverse range of challenges. You will play a pivotal role in developing and implementing LLM applications using machine learning, deep learning, , context engineering, prompting engineering and knowledge base techniques. [Key Responsibilities]: - Collaborate with cross-functional teams to understand project requirements and objectives. - Design and develop end-to-end solutions using LLMs for applications in smart factory and smart city domains. - Integrate LLM applications with structured and unstructured knowledge bases to enhance reasoning and retrieval capabilities. - Apply prompt engineering and context engineering to optimize LLM outputs and align them with business needs. - Conduct fine-tuning, evaluation, and benchmarking of LLM-based models for target use cases. - Stay up-to-date with state-of-the-art research in natural language processing, generative AI, and multi-modal learning. - Evaluate and benchmark different models to identify the best solutions for specific applications. - Share technical knowledge with team members. [Qualifications]: - Master's or Ph.D. in Computer Science, Machine Learning, Deep Learning, or a related field. - Proven experience with large language models (e.g., GPT, LLaMA, Gemini, QWen) and related frameworks. - Strong proficiency in programming languages such as Python, C/C++ and familiarity with relevant libraries (PyTorch, TensorFlow, etc.). - Expertise in prompt engineering, context engineering, and knowledge base integration (e.g., RAG pipelines, vector databases). - Excellent problem-solving skills and the ability to work independently and as part of a team. [Bonus Qualifications]: - Familiarity with VLM. - Familiarity with AI agent framework. - Familiarity with MLOps, model monitoring, and pipeline automation. - Background in smart factory, smart city, or industrial AI use cases. - Contributions to open-source LLM or NLP projects. - Familiarity with Industry 4.0 applications. - Familiarity with vision related work. (Object detection, Segmentation, Recognition...) [What We Offer]: - Flexible working environment - Competitive salary and benefits package. - Opportunity to work on cutting-edge projects with real-world impact. - Collaborative and innovative work environment. - Professional development and training opportunities.

We are seeking a talented and passionate Audio AI Engineer to join our team. You will be responsible for developing, training, and deploying cutting-edge AI models for real-time and audio noise reduction. Your work will directly impact the clarity and quality of our products, from teleconferencing and communication tools to creative audio production and media. The ideal candidate has a strong background in deep learning, a solid understanding of digital signal processing (DSP) fundamentals, and a keen ear for sound. You will collaborate with a cross-functional team of researchers, software engineers, and product managers to bring innovative audio solutions to life. # Responsibilities 1. Design, develop, and train deep learning models (e.g., neural networks) specifically for audio denoising, dereverberation, and speech enhancement. 2. Curate, manage, and preprocess large-scale audio datasets for model training and evaluation. This includes collecting, cleaning, and labeling noisy and clean audio pairs. 3. Optimize AI models for performance, latency, and resource efficiency, ensuring they can run effectively on various platforms, including cloud servers, mobile devices, and embedded systems. 4. Stay up-to-date with the latest research in audio signal processing, machine learning, and generative AI for audio. Explore and prototype new algorithms and techniques to push the boundaries of audio quality. 5. Work closely with the software engineering team to integrate production-ready models into our software and services. Partner with product and design teams to understand user needs and translate them into technical requirements. 6. Develop robust evaluation metrics and conduct rigorous testing (both objective and subjective listening tests) to ensure the denoising models meet high-quality standards. 7. Diagnose and resolve technical issues related to audio processing pipelines and AI model performance. # Requirements 1. Bachelor's, Master's, in Computer Science, Electrical Engineering, Signal Processing, or a related technical field. 2. Proven experience in a role focused on machine learning, with a specialization in audio, speech, or signal processing. 3. Strong proficiency in Python is a must. Experience with C++ is a plus, especially for low-latency, real-time applications. 4. Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow. 5. A solid theoretical and practical understanding of digital signal processing (DSP) concepts, including time-frequency analysis, filter design, and spectral processing. 6. Familiarity with audio editing software like Audacity, Pro Tools, or Adobe Audition for data inspection and analysis. 7. Proficiency with Git. # Preferred Qualifications 1. Experience in a production environment deploying machine learning models into live systems. 2. Knowledge of specific audio denoising techniques and models (e.g., RNNoise, WebRTC, U-Net architectures for audio). 3. Experience with real-time audio systems and APIs. 4. A background in audio engineering or a related field, with an excellent ear for sound quality. 5. Strong mathematical foundation in linear algebra, probability, and statistics. 6. Experience with cloud platforms (AWS, GCP, Azure) and MLOps pipelines. # Soft Skills 1. Excellent problem-solving and analytical skills. 2. Strong communication and collaboration abilities, with the capacity to explain complex technical concepts to non-technical stakeholders. 3. A passion for audio and a creative mindset for solving difficult audio challenges. 4. Ability to work independently and as part of a highly collaborative team. 5. Proficiency in both English and Chinese, written and spoken.

CerenceAI China RD is seeking a Research Engineer to design and implement the next-generation text-to-speech systems and applications. In this role, with members in globe, you will work both frontend (Grapheme-to-phoneme, Text Normalization, phrasing and prosodic control, etc) and backend (acoustic modeling, neural vocoding) components of engine pipelines and end-2-end system for major languages and dialects. Your work will directly impact CerenceAI products ranging from voice assistants to accessibility tools, delivering natural, expressive, and multilingual speech synthesis. Job Description Representative responsibilities/duties will include but not limited to: • Design and optimize text/NLP preprocessing pipelines with Deep Learning or Machine Learning methods, including Grapheme-to-phoneme (G2P) conversion for multilingual support; Text normalization; polyphone disambiguation; Prosody prediction and control • Integrate language models (e.g., BERT, GPT variants) to improve contextual and semantic understanding for natural intonation • Develop rule-based and neural solutions for emotion/style control in synthesized speech • Build state-of-the-art acoustic models (e.g., Tacotron, FastSpeech, VITS) to map linguistic features to spectrograms or waveform parameters. • Optimize neural vocoders (e.g., WaveNet, HiFi-GAN, MelGAN, LPCNet) for high-fidelity, real-time speech synthesis • Optimize inference latencies for both edge devices and cloud platforms • Enhance robustness through noise suppression, speaker adaptation, and multilingual/cross-language/cross -gender voice cloning Knowledge, skills, and qualifications Education: Master in CS, AI, EE, Math, or related field. Required/preferred skills: • hands-on experience in speech generative system development with deep expertise in both frontend and backend components • Proficiency in C/C++ and Python, with mastery of ML frameworks (PyTorch, TensorFlow, etc) • Some background in NLP techniques and/or speech signal processing is welcome • Knowledge on transformer-based language models for prosody prediction • Basic understanding of autoregressive / non-autoregressive acoustic models and neural vocoders • Experience in optimizing models via quantization, pruning, or knowledge distillation • Experience with ONNX Runtime, TensorRT, or TorchScript, etc • Experience with zero-shot/one-shot/few-shot voice cloning or emotional TTS systems • Skilled GPU/TPU cluster and grid user • Fluent English is a must-have

✨ 團隊介紹 91APP是台灣首家掛牌上櫃的 SaaS 軟體服務公司。91APP 為國內第一家「虛實融合 (Online Merge Offline, OMO)」新零售軟體雲服務公司，結合虛實整合並提供線上線下管理工具，協助零售品牌快速切入電商市場，整合線上線下雙向導流、銷售訂單及全通路會員經營數據，快速增強營運效率提升獲利。 在 91APP 的資料科學團隊，我們擁有的是研究不完的案例，你可以了解每一家品牌是如何從剛起步擴展到月業績破千萬，你可以仔細研究並探討其每個階段的關鍵原因，然而這些有趣的小結果都將內化堆疊成為你的產業知識，或是變成標準軟體產品提供給全台灣甚至全世界的品牌使用。 在這裡，你有機會站在第一線直接面對世界級的品牌對他們講述你從數據中發現精彩萬分的商業故事；你也可能在產品團隊中跟你的產品經理、使用者經驗設計師與開發團隊們討論你苦心研究多時的數據模型需要如何對市場溝通、要設計什麼流程來吸引更多品牌使用以及要如何將你的模型部署至正式環境。這些內容將讓你不僅保有商業現場的敏銳度也同時具有軟體開發的技術力。當然，無論你想往前（商業現場）多跨一步或是往後（產品開發）多踩一腳，我們都有如同任意門般的溝通管道以及循序漸進的計畫能夠輔助你達到你想要的職涯目標。 ✨ 你將負責的任務 1.與數據科學家 (DS)、產品經理和其他技術團隊密切合作，設計並部署 AI 演算法與模型應用服務，解決 91APP 的各種商業問題 2.設計並開發高效且可擴展的模型服務，確保模型成果能夠在大規模生產環境中穩定運行，並可供產品線、第三方合作夥伴或品牌使用 3.針對不同商業場景與需求，設計與建置 AI Service，包含資料前處理、feature engineering 與 model inference 等，提供不同產品線、第三方合作夥伴或是品牌使用模型服務 4.學習 AI/ML 最新技術、進行實作，並透過實際商業問題的 PoC 評估可行性 5.實踐 MLOps 進行 Model Performance 監控、re-training 與模型版控 ✨ 我們希望你具備 1.至少 2 年 Data 或 1 年 Backend 相關開發經驗，具有 FastAPI 設計與開發經驗尤佳 2.熟練至少一項以下程式語言 e.g. Python, Java 或 Node.js 等 3.熟悉 DevOps 實踐，具備 git 版控、 CI/CD pipeline 使用經驗，確保模型和系統的穩定 部署與持續交付 4.熟悉 GCP，包含：Vertex AI、Bigquery、Cloud Functions、Cloud Run、GKE… 5.了解基本統計學、主流機器學習與 AI 演算法核心原理（Probability、LSH 、 similarity、Logistic Regression、KMeans、DNN、CNN、RNN、NLP…） 6.具備設計和實現安全、高效 API 的經驗，確保服務在多方合作的環境中保持高可用性和 數據安全性 7.保持對新技術的敏感度，熱衷於學習和分享最新的 AI/ML 技術與方法，並積極應用於解 決實際商業問題，以驅動創新和提升產品競爭力 ✨ 關於我們的團隊文化 91APP 的工作日常 = 學習 × 成長 × 歡樂 在 91APP，好的工作氛圍不只是空間，而是大家一起「學、問、成長」的日常 ✔ 一起學與分享：讀書會、學習社群遍地開花，讓知識自然流動 ✔ 擁抱改變、持續成長：勇於嘗試新工具、投資在人的成長 ✔ 為長遠而建：做事不求快，而求穩；每次改進都讓未來更順 ✔ 讓討論更有方向：鼓勵提問、釐清問題，讓合作更有效率 ✔ 科技以人為本：用AI放大人的影響力，讓成果更貼近使用者 ✨到職後我們提供 ✔ 完整的新人訓練計畫 ✔ 資深工程師指導 (Mentor 制度) ✔ 定期AI技術分享與討論，分享最新 AI 開發工具與應用 ✔ 先進的 AI 開發環境，團隊已將 AI 深度整合至開發流程 ✔ 參與開發 AI 功能的機會，站在技術前沿 ✔ 持續學習與成長的機會，清晰的職涯發展路徑 ✨ 更多技術動態與分享，歡迎追蹤 91APP Tech FB：https://www.facebook.com/91apptech

【工作內容】 1. Architect, design, and develop AI agentic systems 【需求條件】 1.Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, or a related field. 2.Experience with RAG/MCP and backend code-generation 【加分條件】 1.Strong understanding of software data structures, algorithms, and proficiency in object oriented coding, preferably in C or C++. Exposure to AI/ML models, accelerators is a plus. 2.Familiarity with PyTorch, Tensorflow, ML models 3.Fluency in English 【工作地點】:台北/南投/WFH

We are looking for a Machine Learning (ML) Engineer to help us create artificial intelligence audio products. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. Responsibilities ● Design machine learning model for audio applications (like noise reduction / speech separation / speech recognition). ● Research and implement appropriate ML algorithms and tools. ● Develop and optimize ML applications according to requirements. ● Run machine learning tests and experiments. ● Perform statistical analysis and fine-tuning using test results. Requirements and skills ● Proven experience as a Machine Learning Engineer or similar role. ● Deep knowledge of math, probability, statistics and algorithms. ● Advanced proficiency with Python; Familiarity with C/C++ is a plus. ● Familiarity with machine learning frameworks (like Keras / Tensorflow /PyTorch) and libraries (like scikit-learn). ● Great communication and collaboration skills. ● Outstanding analytical and problem-solving skills. ● Excellent time management and organizational abilities.

Our client is a 50+ year old company that delivers industry leading clinical trial endpoint technology solutions. The future of clinical trials is vibrant, with new technologies revolutionizing what’s possible. From new trial modes to faster and integrated evidence and findings, our innovative clinical trial solutions mean we can unlock better evidence. As an Algorithm Engineer, your primary responsibility is to serve as a development team member customizing products to meet the client’s requirements on a cross-functional project team. Moreover, you will be working on medical imaging processing pipelines for novel studies and improving data quality in the context of clinical trials. You will work with the most talented engineers, scientists, and medical domain experts across the world 【What You'll be doing】 • Algorithms integration toward different platforms, including the cloud computation service, and the in-house Java-based system • Support troubleshooting application issues • Medical imaging processing pipeline development • Enhance and maintain the in-house Java-based system 【Key Responsibilities】 Ownership of our Image Processing Pipelines: • Ensure the smooth operation of image processing pipelines • Identify and resolve issues promptly to minimize disruptions Platform Improvement • Enhance platform capabilities through the implementation of improved monitoring tools • Work on scalability solutions to accommodate the increasing volume of medical images • Develop troubleshooting tools to streamline issue resolution processes Algorithm Integration: • Collaborate with scientific and AI teams to integrate new algorithms into our image processing workflows • Optimize algorithm robustness and performance for enhanced efficiency and accuracy 【What we look for】 • Strong experience with Python. Familiarity with C/C++ / Java and SQL a plus • Good command of Linux environments and system administration • Experience in Software Development Lifecycle, and familiar with Jira, version control, unit-tests, CI/CD • Experience in the scientific field and an interest in medical topics • Effective communication skills in English, both written and verbal • Strong organizational skills and a detail-oriented work ethic

本公司核心為AI技術解決方案，改變人們的生活品質，目前致力研發專注於智慧助聽技術與人工智慧視覺應用類別的產品。 【工作內容】 1. 結合深度學習（DL）與傳統電腦視覺，研發影像強化、物件偵測、物件分割等相關技術，並實作於 Edge Device。 2. . 完成主管交辦事項。 【職務需求】 1. 具備人工智慧與電腦視覺開發經驗。 2. 熟悉 C/C++ （尤佳）。 3. 熟悉 OpenCV。 4. 至少擅長一項深度學習框架 （如：Pytorch、Tensorflow）。 5. 具 Git 版本控制知識。 6. 具獨立開發能力。 7. 具良好團隊合作能力，有意願與團隊夥伴分享技術知識。 【加分項目】 1. 具 Embedded System 系統整合經驗。 2. 有布署 AI 模型至嵌入式系統經驗。 3. 熟悉 AI 模型剪技、量化、蒸餾等。