AI/ML Engineer 人工智能/机器学习工程师

• Employees can work remotely
• Full-time
• Workplace Type: Remote
• City: Cebu

Company Description 公司简介

Official website: https://www.qima.com/

Key Responsibilities: 关键职责：

• AI/ML Solution Implementation: Work closely with business leaders and data scientists to understand user needs and transition AI/ML prototypes into production-ready solutions
  人工智能/机器学习解决方案实施：与业务领导者和数据科学家紧密合作，了解用户需求，将 AI/ML 原型过渡到生产就绪的解决方案
• Full-Scale Model Deployment: Design, develop, and deploy scalable machine learning models and algorithms to solve complex business problems.
  全面模型部署：设计、开发并部署可扩展的机器学习模型和算法，以解决复杂商业问题。
• Data Integration: Ensure efficient collection and integration of data from diverse sources for training and validation of AI models.
  数据集成：确保高效收集和整合来自不同来源的数据，用于 AI 模型的训练和验证。
• System Integration: Collaborate with tech teams to integrate AI/ML solutions seamlessly into existing systems and enhance data collection processes.
  系统集成：与技术团队协作，将人工智能/机器学习解决方案无缝集成到现有系统中，并提升数据收集流程。
• Performance Optimization: Continuously monitor and optimize model performance to ensure responsiveness and scalability.
  性能优化：持续监控和优化模型性能，确保响应性和可扩展性。
• Code Quality and Maintenance: Write clean, maintainable, and well-documented code, ensuring best practices in software development.
  代码质量和维护：编写清晰、可维护且文档齐全的代码，确保软件开发的最佳实践。
• Process Improvement: Leverage AI/ML to identify opportunities for process improvement and contribute to strategic projects aimed at enhancing business performance and competitiveness.
  流程改进：利用人工智能/机器学习识别流程改进的机会，并参与旨在提升业务绩效和竞争力的战略项目。
• Change Management and Adoption: Ensure successful adoption of AI/ML solutions by managing organizational change, assisting with user training, and conducting post-implementation follow-up to support users and address any issues.
  人工智能/机器学习解决方案的变革管理与采纳：通过管理组织变革、协助用户培训以及实施后跟进以支持用户并解决任何问题，确保人工智能/机器学习解决方案的成功采纳。

Qualifications 资格

Required Skills: 所需技能：

• Education and Experience: A bachelor's or master's degree in Computer Science, Software Engineering, Data Science, or a related field, with at least 3+ years of experience in software development, including some experience with AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  教育及经验：计算机科学、软件工程、数据科学或相关领域的学士学位或硕士学位，至少 3 年以上软件开发经验，包括使用 TensorFlow、PyTorch 或 scikit-learn 等 AI/ML 框架的经验。
• Programming Skills: Strong proficiency in Python and experience with relevant libraries (NumPy, Pandas, TensorFlow, PyTorch, Keras, etc.). Knowledge of additional languages like Java, C++, or SQL is a plus.
  编程技能：熟练掌握 Python，并具备相关库（NumPy、Pandas、TensorFlow、PyTorch、Keras 等）的使用经验。了解 Java、C++或 SQL 等其他语言也是加分项。
• AI/ML Fundamentals: Foundational understanding of machine learning concepts, including supervised and unsupervised learning, deep learning, and model evaluation techniques.
  人工智能/机器学习基础：机器学习基本概念的理解，包括监督学习、无监督学习、深度学习以及模型评估技术。
• Data Handling: Proficiency in data preprocessing and feature engineering.
  数据处理：精通数据预处理和特征工程。
• Cloud Platforms: Familiarity with cloud computing platforms (AWS, Azure, Google Cloud) and containerization technologies (Docker, Kubernetes).
  云计算平台：熟悉云计算平台（AWS、Azure、Google Cloud）和容器化技术（Docker、Kubernetes）。
• Analytical Skills: Excellent analytical skills, with the ability to interpret complex datasets and derive actionable insights.
  分析能力：具备出色的分析能力，能够解读复杂的数据集并得出可操作的见解。
• Communication Skills: Excellent verbal and written communication skills, with the ability to effectively collaborate with cross-functional teams and stakeholders
  沟通技巧：具备优秀的口头和书面沟通能力，能够有效地与跨职能团队和利益相关者协作

Preferred Skills (not mandatory):
推荐技能（非强制性）：

• Natural Language Processing (NLP): Experience with NLP, generative AI and their applications.
  自然语言处理（NLP）：具有 NLP、生成式 AI 及其应用的经验。
• Computer Vision: Knowledge of computer vision techniques and applications.
  计算机视觉：掌握计算机视觉技术和应用知识。
• Quality Management: Experience in quality management, laboratory testing processes, supply chain management, or quality assurance.
  质量管理：在质量管理、实验室检测流程、供应链管理或质量保证方面的经验。