• Chris Armbruster

Deep Learning Engineer (m/f/d). A competency profile.

Updated: May 9

The competency profile validates your domain expertise in data. It recognizes you as a Senior practitioner or advances your career to the Senior level.

By practitioners, for practitioners - this service is provided by AI Guild members recognized for their expertise.

Here is the example of a Deep Learning engineer.

She has been in the industry for three years, with prior programming experience based on academic research and project work. She is at a startup, and computer vision technologies drive product development and deployment.


What do you see in the competency profile?

This profile shows substantial, deep expertise in two fields:

  • Developing and deploying CNN models; and

  • Innovating on Deep Learning models by building on research advances.

She flanks her focus on modeling by competence in

  • Image processing, which is vital to the quality of the models; and

  • Best practice in building the solution, which secures quality deployment.

It is the profile of an accomplished data practitioner that is a Senior, or at least ready to be a Senior. It was built as part of the AI Guild career development program.

Focus: What is in and what has been left out?

A competency profile is short and sharp. Perhaps you noticed that the profile is not full of buzzwords but seeks to convey specific expertise in simple terms (e.g., 8 CNN deployed). We didn't include a long list of technical skills (as you might on a CV) so that it might be easier to see: I am an expert for building and deploying innovative deep learning models.

As a practitioner, the challenge is to focus. Typically, one seeks to highlight the breadth of skills. Moreover, there are many new and updated tools, which entices you to stay up-to-date broadly. These issues have given rise to the oxymoron of the 'full-stack data scientist.' Yet, to be a Senior or make your case to be a Senior, you must focus. This profile has a great focus on deep learning with a track record in computer vision, image processing, and visual search.

Senior in Deep Learning or Computer Vision?

Her practice seems to be related mainly to images and computer vision, so is this not the Computer Vision engineer profile? I imagine that companies looking to hire a Computer Vision expert are interested. However, the competency profile conveys a broader interest in Deep Learning that may include language or numbers as data.

Where is her #datacareer headed?

A competency profile ideally also includes a sense of direction. Both the profile statement and selection of expertise convey a sense of mission: This data practitioner wants to keep innovating at the forefront of modeling. Innovation here means not academic work but rather working on prototypes that have a realistic chance of being deployed because they drive a solution for a recognized customer or business need.

How to get your competency profile?

Are you in Year 2, 3, or 4 of your #datacareer? Would you like to find out how you efficiently show and develop your expertise? It takes 60 days to complete the competency profile. All you need to do to start is point us to your LinkedIn or GitHub profile (or similar) here.

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