Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.
Job Responsibilities/ 工作职责 :
Responsibilities:
- Collaborate with stakeholders to understand business objectives and define problems that can be addressed through machine learning and artificial intelligence.
- Collect, preprocess, and analyze large datasets to extract meaningful patterns and insights.
- Choose appropriate machine learning algorithms based on the nature of the problem, dataset characteristics, and desired outcomes.
- Develop and train machine learning models using programming languages like Python or R and frameworks such as TensorFlow or PyTorch.
- Identify and engineer relevant features from the data to enhance the predictive capabilities of machine learning models.
- Integrate machine learning models into existing systems or develop new applications that leverage machine learning capabilities.
- Optimize machine learning solutions for scalability and efficiency, particularly when dealing with large-scale datasets or real-time applications.
- Collaborate with cross-functional teams, including data scientists, software engineers, and business analysts.
- Stay informed about the latest advancements in machine learning, artificial intelligence, and related technologies.
- Address ethical considerations related to bias, fairness, and privacy in machine learning models.
- Maintain comprehensive documentation for machine learning models, including code, model architectures, and parameters.
- Implement security measures to protect machine learning models and data from potential vulnerabilities.
- Establish monitoring mechanisms to track the performance of deployed machine learning models over time.
Requirements:
- Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related field.
- Proficiency in programming languages such as Python or R.
- Experience with machine learning frameworks like TensorFlow or PyTorch.
- Strong understanding of statistical analysis and data mining techniques.
- Ability to preprocess and analyze large datasets.
- Experience in developing and deploying machine learning models to production environment that serve millions of end users.
- Familiarity with software development practices and version control systems.
- Excellent problem-solving skills and attention to detail.
- Strong communication and teamwork abilities.
Preferred Qualifications:
- Experience with deep learning architectures and algorithms.
- Knowledge of big data tools and platforms.
- Familiarity with cloud services related to machine learning.
- Publications or contributions to the machine learning community.
- Proven track record of implementing, maintaining and optimizing production machine learning models.
岗位职责：
- 与相关利益方合作，理解业务目标，并定义可通过机器学习和人工智能解决的问题。
- 收集、预处理和分析大规模数据集，以提取有意义的模式和见解。
- 根据问题类型、数据集特性和预期结果选择合适的机器学习算法。
- 使用Python 或 R等编程语言以及TensorFlow 或 PyTorch等框架开发和训练机器学习模型。
- 识别和工程化关键特征，以增强机器学习模型的预测能力。
- 将机器学习模型集成到现有系统，或开发新的应用程序以利用机器学习能力。
- 针对大规模数据集或实时应用场景，优化机器学习解决方案，提升可扩展性和计算效率。
- 与跨职能团队（如数据科学家、软件工程师、业务分析师）协作。
- 关注机器学习、人工智能及相关技术的最新进展。
- 解决机器学习模型中涉及的公平性、偏差和隐私保护等伦理问题。
- 维护机器学习模型的全面文档，包括代码、模型架构和参数。
- 实施安全措施，保护机器学习模型和数据免受潜在漏洞的影响。
- 建立监控机制，持续跟踪已部署机器学习模型的运行表现。
岗位要求：
- 计算机科学、数学、统计学或相关领域的学士或硕士学位。
- 熟练掌握Python 或 R等编程语言。
- 具备使用TensorFlow 或 PyTorch等机器学习框架的经验。
- 深入理解统计分析和数据挖掘技术。
- 能够预处理和分析大规模数据集。
- 具备开发和部署机器学习模型到生产环境的经验，能够支持百万级终端用户。
- 熟悉软件开发实践和版本控制系统。
- 具备优秀的问题解决能力和高度的细节关注度。
- 具备良好的沟通能力和团队协作能力。
优先条件：
- 具备深度学习架构和算法的经验。
- 了解大数据工具和平台。
- 熟悉云服务中的机器学习解决方案。
- 在机器学习领域有论文发表或社区贡献经验。
- 具备实施、维护和优化生产环境机器学习模型的成功案例。
Pre-Requisites/ 任职要求 :
Are you game?
