Companies who rely on a workforce to perform operations in the physical world are often blind with respect to what is really happening on the field. The tools they use do not allow to collect complete and accurate feedbacks and it is difficult for those companies to understand the source of errors and inefficiencies in their field processes.
Deepomatic develops a Field Vision Platform to allow our clients to automatically make sure that field reports are filled with the accurate informations, thanks to AI. The platform also centralizes all those reports, which can then be mined by our clients to understand how they can improve their quality of service.

We are looking for a MLOps Engineer to join our product team and help us deliver tools to allow our platform’s user to be more productive when designing their own computer vision pipelines. Here are a few examples of the challenges you might be confronted to:

• How do you improve the performance of our algorithms (new data-augmentation technics, new models, new losses, hyper-parameter automatic tuning, etc…)?
• How do you quantize neural networks so that they are efficient on both mobile or embedded devices?
• How do you help a non-expert user of the platform to understand how to act to improve its computer vision application ?
  Besides developing Deepomatic’s AI back-end, your role will also typically consist of taking part and animating internal reading groups as well as contributing to external tech/deep-learning evangelism.

Within 1 month, you will:

• Learn everything there is to know about the business and the technology behind it. You will learn how our products work, how to deploy them, how to debug them.
• Dig into the code of training back-end
• Learn to use our internal tools to collaborate effectively with all Deepomatic teams
• Start and complete your Onboarding Project, which all new employees do within their first month, and ship your first features.

Within 3 months, you will:

• Be familiar with the training back-end and its various components
• Implement a new entier capability or research paper with success
• Help our “Solution Architects” to transition to your newly deployed feature

Within 6 months, you will:

• Monitor and improve performance of algorithms: work on speed and accuracy improvements, solve production issues and scaling needs.
• Contribute to the two systems (Data management & Deployment) which interact with our training back-end.
• Help design specifications of the next features of the platform.
• Help with hiring new talents

Within 1 year, you will:

• Be the go-to person regarding technical issues and contribute to the design of its architecture.
• Mentor new team members.
• Help structure the team by improving existing processes and tools, and setting objectives for the team.

• 3+ years of experience in back-end development.
• 2+ years of experience in machine learning and/or deep learning.
• Experience in Python
• Experience in Tensorflow or Pytorch
• Excellent problem-solving attitude.
• Great human qualities and a love for teamwork.
• Great oral and written communication in English.

Screening call
Technical test at home
Final round of on-site interviews with technical tests, a culture-fit interview, and a product demo