A machine learning (ML) developer is an expert on using data to training models. The models are then used to automate processes like image classification, speech recognition, and market forecasting.
A machine learning (ML) developer is an expert on using data to training models. The models are then used to automate processes like image classification, speech recognition, and market forecasting.
Definitions of machine learning roles can vary. Often there’s some conceptual overlap or even conflation with the roles of data scientist or artificial intelligence (AI) engineer. 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.
Machine Learning Developer - Job Description and Ad Template
Copy this template, and modify it as your own:
Company Introduction
{{ Write a short and catchy paragraph about your company. Make sure to provide information about the company’s culture, perks, and benefits. Mention office hours, remote working possibilities, and everything else that you think makes your company interesting. }}
Job Description
We are looking for an expert in machine learning to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
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, along with metrics to track their progress
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
Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Finding available datasets online that could be used for training
Defining validation strategies
Defining the preprocessing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyperparameters
Analyzing the errors of the model and designing strategies to overcome them
Deploying models to production
{{Add any other relevant responsibilities here}}
Skills
Proficiency with a deep learning framework such as TensorFlow or Keras
Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
Expertise in visualizing and manipulating big datasets
Proficiency with OpenCV
Familiarity with Linux
Ability to select hardware to run an ML model with the required latency
{{Make sure to mention any other frameworks, libraries, or other technologies relevant to your project}}
{{List any education level or certification you may require}}
Machine Learning Engineers are experts in building, designing and optimizing artificial intelligence (AI) systems. This guide to hiring Machine Learning Engineers features interview questions and answers, as well as best practices that will help you identify the best candidates for your company.
Toptal is a marketplace for top machine learning engineers. Top companies and start-ups choose Toptal machine learning freelancers for their mission-critical software projects.
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United StatesToptal Member Since November 17, 2015
Necati is a computer scientist with 17 years of experience in the private industry, focusing on DevOps and machine learning. He is also an AWS Certified Solutions Architect and AWS Certified Machine Learning Specialist with a PhD in computer engineering. He has led teams and driven infrastructural and architectural decisions for the last ten years. Necati also takes an active role in the implementation and design phases of the infrastructure, architecture, and process.
