Machine Learning Engineer
经验最低限度：在软件开发领域有经验2年以上 · 强大的分析和解决问题的技能 · Python 和 SQL 的专家 · 现代软件开发最佳实践的经验，例如 ·敏捷软件开发 · 代码审查 · 单元测试 · 版本控制，如 git · CI/CD · 微服务架构的经验 · 在敏捷团队工作的经验 • ML 框架和工具 （比如熊猫，木偶，scikit-learn, TensorFlow, Pytorch,SparkML）的经验 · 与现代 ETL,计算和编排框架的经验；比如 Apache Spark,Apache Flink,Kafka 等 · 开发经验 Windows 和 Linux. · 经验与容器技术，例如 Docker,Kubernetes 理想：· 在构建机器学习或人工智能系统的经验 · R 语言熟练 · 在生产中部署模型的经验 • 在构建分布式系统的经历 · 在 NoSQL 数据库的经验• 与 ML 平台的工作经验，如 MLflow,Kubeflow 等 · 在 Data Science 平台 （例如 Dataiku,Domino 等）的经验 · 在云基础设施，如 Azure,AWS,GCP 方面的经验；最好是 AWS 资格 （最小）·信息技术相关资格 -计算机科学或工程资格 （理想或优先）. · 信息技术士学位 - 数据科学或工程学 - 其它知识 最少：必须了解以下内容：· 对象导向和功能编程在 python 中 ·现代软件开发实践 · 使用 SQL 的数据库查询 · 数据生命周期 ·机器学习概念 ·机器模型生命周期 · 微服务架构理想情况：对：· 数据科学生命周期 · 分布系统设计 · 大数据存储和处理解决方案 ·机器模式架构技能 ·分析能力 ·决策技巧 ·规划，组织和协调技巧 · 问题解决技巧 · 研究技巧 原创发布于喜马拉雅山
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Experience
Minimum:
Proven experience in:
- 2+ yrs software development experience
- Strong analytical and problem-solving skills
- Expert in Python and SQL
- Experience with the modern software development best practices, e.g.
- agile software development
- code reviews
- unit testing
- version control, e.g. git
- CI/CD
- Experience with microservice architectures
- Experience working in an agile team
- Experience with ML frameworks and tools (e.g. pandas, numpy, scikit-learn, TensorFlow, Pytorch, Spark MLlib)
- Experience with modern ETL, compute and orchestration frameworks, e.g. Apache Spark, Apache Flink, Apache Kafka, etc.
- Development experience in both Windows and Linux
- Experience with container technologies, e.g. Docker, Kubernetes
Ideal:
- Experience in building machine learning or AI systems
- Proficiency in R language
- Experience deploying models to production
- Experience building distributed systems
- Experience with NoSQL databases
- Experience working with ML platforms, e.g. MLflow, Kubeflow, etc.
- Experience working with Data Science platforms, e.g. Dataiku, Domino, etc.
- Experience with cloud-based infrastructure, e.g. Azure, AWS, GCP; ideally AWS
Qualifications (Minimum)
· A relevant qualification in Information Technology - Computer Science or Engineering
Qualifications (Ideal or Preferred)
· Masters Degree in Information Technology - Computer Science or Engineering - Other
Knowledge
Min:
Must have knowledge of:
- Object oriented and functional programming in Python
- Modern software development practices
- Database querying using SQL
- Data life cycle
- Machine learning concepts
- Machine learning model life cycle
- Microservice architectures
Ideal:
Knowledge of:
- Data Science lifecycle
- Distributed system design
- Big data storage and processing solutions
- Machine learning model architectures
Skills
- Analytical Skills
- Decision making skills
- Planning, organising and coordination skills
- Problem solving skills
- Researching skills
Originally posted on Himalayas