Machine Learning

机器学习工程师职位描述模板

A machine learning (ML) developer is an expert on using data to training models. 然后,这些模型被用于自动处理图像分类等过程, speech recognition, and market forecasting.

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A machine learning (ML) developer is an expert on using data to training models. 然后,这些模型被用于自动处理图像分类等过程, speech recognition, and market forecasting.

机器学习角色的定义可以有所不同. 通常会有一些概念上的重叠,甚至与角色的混淆 data scientist or 人工智能(AI)工程师. Machine learning is actually a subfield of AI that focuses on analyzing data to find relations between the input and the desired output.

A machine learning developer produces a tailor-made solution for each problem. The only way to achieve optimal results is to carefully process the data and select the best algorithm for the given context.

机器学习开发人员-职位描述和广告模板

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Company Introduction

{{写一段简短而醒目的关于你公司的文字. Make sure to provide information about the company’s culture, perks, and benefits. Mention office hours, remote working possibilities, 以及所有你认为能让你的公司有趣的东西. }}

Job Description

We are looking for an expert in machine learning to help us extract value from our data. 你将领导从数据收集开始的所有过程, cleaning, and preprocessing, 训练模型并将其部署到生产环境中.

The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.

{{ Describe the project and the type of data (images, audio, text, tables…) }}

Responsibilities

  • Understanding business objectives and developing models that help to achieve them, 还有跟踪进度的指标
  • Managing available resources such as hardware, data, and personnel so that deadlines are met
  • Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
  • 探索和可视化数据,以获得对它的理解, then identifying differences in data distribution that could affect performance when deploying the model in the real world
  • 验证数据质量,并/或通过数据清理确保数据质量
  • 如果需要更多的数据,监督数据采集过程
  • 在网上找到可用的数据集,可以用于培训
  • Defining validation strategies
  • Defining the preprocessing or feature engineering to be done on a given dataset
  • 定义数据增强管道
  • 训练模型并调整它们的超参数
  • Analyzing the errors of the model and designing strategies to overcome them
  • Deploying models to production
  • {{在这里添加任何其他相关职责}}

Skills

  • 熟练使用深度学习框架,如TensorFlow或Keras
  • Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
  • 具有可视化和操作大数据集的专业知识
  • Proficiency with OpenCV
  • Familiarity with Linux
  • 能够选择硬件以运行具有所需延迟的ML模型
  • {{确保提及任何其他框架, libraries, 或其他与您的项目相关的技术}}
  • {{列出您可能需要的教育程度或证书}}
See also:Toptal不断增长的社区驱动列表 基本的机器学习面试问题

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