Microchip Microchip

Senior/​Lead Deep Learning Engineer

Time zone



Full-time, remote

Personal recruiter

Anastasiia Zhuk


Deep Learning


Product Vacancies for products developed by TeamDev

About the project

We invite an experienced Deep learning Engineer to join the team working on our commercial product — Pure Photos. It’s the service for analyzing and processing a large number of photos. 

The product is already one of the bests in the field and strives to dominate. We process about 300 thousand images per month, and this is only the beginning. By developing AI, we solve and automate tasks that previously could only be performed with human participation. The product helps professional photographers automatically process photos. The main function is to remove background from photos. And we have more ideas to expand the functionality, for example, retouching and color correction.  You can try it for free on the site and see the top quality provided for yourself. 


processed images a month


releases a year


merged PRs a year


commits a year


types in API

The team

  • 4

    Deep Learning Engineers

  • 3

    Web Ninja

Processes and instruments

Pure Photos team has built an elaborate system, which is based on the state of the art deep learning and computer vision algorithms. It provides an AI-based solution for recognizing images of people located on the most complicated outdoors backgrounds, and extracting them with surgical precision.

The solution was conceived and built from the ground up using Google Cloud Platform Services. We’re utilizing Google Compute Engine for our deep learning training as well as inference using the latest GPUs. Moreover, the Pure Photos team has built a custom solution that allows scaling up instances in different regions and zones with the ability to utilize preemptible VMs, which reduces the costs dramatically.

The application is built with the event-based approach built on top of the Spine Event Engine CQRS/ES framework. Pure Photos has all the business logic hosted in various AppEngine microservices as well as the front-facing web application. This allows us to handle almost any load with automatic upscale. Minimizes costs when the number of clients is low with the ability to downscale to 0.

We use modern CI/CD tools such as Terraform and Packer that allow us to implement an “Infrastructure as a code” approach and automate deployments.

  • Java, JavaScript, TypeScript, Python, NodeJs, and Vue.
  • JUnit, Mocha, Karma.
  • DDD, CQRS, Event Sourcing, Spine Framework.
  • IntelliJ IDEA, WebStorm, PyCharm.
  • Git, GitHub, GitHub Actions.
  • Google Cloud Platform, Firebase platform, Terraform, Packer, Docker.

Our principles

In our daily work and when making key decisions, we are guided by the following principles:

  • Confidence. We trust each other and our clients trust us.
  • Support. We support each other in order to achieve our goals and boost professional growth as a team and as an individual.
  • Quality. We pay attention to what and how we develop. We want to be satisfied with the results of our work.
  • Flexibility. We are ready to adapt to changes if needed.
  • Fun. We strive to enjoy what we do.

What you will do on this project?

Create and train deep learning models for computer vision: image classification, semantic segmentation, computational photography.

Knowledge and skills required

  • 5+ years of experience in Engineering.
  • 3+ years of experience in Deep Learning Engineering.
  • Deep knowledge in math (linear algebra, calculus), Deep Learning, and Computer Vision.
  • Experience with Python.
  • Knowledge of PyTorch, NumPy, OpenCV, TensorFlow.
  • Experience with Linux.

Would be a plus

  • Experience in using NLP.
  • Experience with Google Cloud Engine.

Work environment

We provide a comfortable environment for work, development, and training of every employee. 2020 has taught us to work remotely and be a team, being 1000 kilometres apart. Now we use it to the fullest building our distributed work process.

  • Flexible schedule.

  • Online English language courses.

  • Compensation for business trips to the USA and Europe.

  • Compensation for participation in professional conferences and educational programs.

  • Constantly updated technology library.

  • Compensation package: 20 paid days for rest and 5 paid days for sick leaves.

Microchip Microchip

What's next?


Response to the vacancy. You will receive a response to your resume, within one or two business days. We might clarify some details, schedule a video call or give a feedback.


The first meeting. Video call with a recruiter, where we get to know each other better.


Technical interview. Interview with members of your future team. Here you will have the opportunity to learn more about the project and its technical details. Within a few days after the interview, we exchange feedback.


Offer. We announce our offer during the video call. At this stage, you and us can once again discuss all the issues of interest in order to make a balanced decision about cooperation.

Thanks for the application!

Our recruiter will contact you as soon as possible.

In order to pleasantly pass the time of waiting and get to know each other better:

“Вёрстка — это не тупо”

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“How to write emails”

PDF-Recommendations for Customer Correspondence.


Our educational project in domain-oriented design.

Job application

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