understandAI GmbH

Software Development

51-200

Germany

## Keywords

MLOps | Cloud | Kubernetes

## The role

As a MLOps-engineer at UAI, you enable the machine learning engineers to build, operate and ship models and to manage data in an efficient way. Having teams that are responsible for a product end to end, you will work in a team of machine learning engineers and collaborate closely with our DevOps experts across teams.

The role is a blend of system and software engineering where coding and automation are essential. Furthermore you can drive the implementation of particular solutions and distribute your knowledge to the other team-members. You embody the philosophies of DevOps with a greater focus on measuring and achieving reliability through engineering and operations work.

## Your tasks

* Build and maintain the next generation of our ML infrastructure catering for...  
   * Model development  
   * Data management  
   * Model operation and management and monitoring  
   * Cost transparency
* Provide developer friendly tools to enable ML engineers
* Drive the implementation together with ML engineers
* Collaborate closely with our DevOps experts
* Promote MLOps mindset in the team
* Constantly evaluate state of the art MLOps solutions for our use case
* Identify automation opportunities to gain efficiency, reliability, and scalability

## What will you need to be successful?

* Experience with MLOps tools
* Strong experience with at least one cloud provider – we are using Google Cloud
* Experience with Kubernetes
* At least basic understanding of machine learning
* Solid experience in one high-level language, e.g. Python, JavaScript, Java, or similar
* Large-scale system design exposure, in-depth understanding of UNIX/Linux, network technology, and security practices
* Ability to lead initiatives and motivate people
* Enjoy working in a team and actively communicating with your colleagues
* Education, job experience, and special requirements
* University degree in Computer Science (or related) or a proven track record as a MLOps expert
* Good communication skills in English both verbal and written

## What we offer

* A crucial role in a dynamic and fast-growing team
* A work environment that fosters trust, respect, and feedback
* An onboarding buddy to integrate you smoothly into our team
* Productivity and improvement time between the development sprints
* A mentor helping you with your personal goals, technical progress in general and your software engineering skills in particular
* Free snacks, drinks, and the option to join activities like hiking, inline-skating, climbing or board game nights
* Competitive salary, flexible working hours, work from home

## Overview of our tech stack

Google Cloud, Kubernetes, Terraform, ArgoCD, Docker, Python, Typescript

Employee

Professional / Experienced

<h2 id="keywords">Keywords</h2>
<p>MLOps | Cloud | Kubernetes</p>
<h2 id="the-role">The role</h2>
<p>As a MLOps-engineer at UAI, you enable the machine learning engineers to build, operate and ship models and to manage data in an efficient way. Having teams that are responsible for a product end to end, you will work in a team of machine learning engineers and collaborate closely with our DevOps experts across teams.</p>
<p>The role is a blend of system and software engineering where coding and automation are essential. Furthermore you can drive the implementation of particular solutions and distribute your knowledge to the other team-members. You embody the philosophies of DevOps with a greater focus on measuring and achieving reliability through engineering and operations work.</p>
<h2 id="your-tasks">Your tasks</h2>
<ul>
<li>Build and maintain the next generation of our ML infrastructure catering for...  <ul>
<li>Model development  </li>
<li>Data management  </li>
<li>Model operation and management and monitoring  </li>
<li>Cost transparency</li>
</ul>
</li>
<li>Provide developer friendly tools to enable ML engineers</li>
<li>Drive the implementation together with ML engineers</li>
<li>Collaborate closely with our DevOps experts</li>
<li>Promote MLOps mindset in the team</li>
<li>Constantly evaluate state of the art MLOps solutions for our use case</li>
<li>Identify automation opportunities to gain efficiency, reliability, and scalability</li>
</ul>
<h2 id="what-will-you-need-to-be-successful">What will you need to be successful?</h2>
<ul>
<li>Experience with MLOps tools</li>
<li>Strong experience with at least one cloud provider – we are using Google Cloud</li>
<li>Experience with Kubernetes</li>
<li>At least basic understanding of machine learning</li>
<li>Solid experience in one high-level language, e.g. Python, JavaScript, Java, or similar</li>
<li>Large-scale system design exposure, in-depth understanding of UNIX/Linux, network technology, and security practices</li>
<li>Ability to lead initiatives and motivate people</li>
<li>Enjoy working in a team and actively communicating with your colleagues</li>
<li>Education, job experience, and special requirements</li>
<li>University degree in Computer Science (or related) or a proven track record as a MLOps expert</li>
<li>Good communication skills in English both verbal and written</li>
</ul>
<h2 id="what-we-offer">What we offer</h2>
<ul>
<li>A crucial role in a dynamic and fast-growing team</li>
<li>A work environment that fosters trust, respect, and feedback</li>
<li>An onboarding buddy to integrate you smoothly into our team</li>
<li>Productivity and improvement time between the development sprints</li>
<li>A mentor helping you with your personal goals, technical progress in general and your software engineering skills in particular</li>
<li>Free snacks, drinks, and the option to join activities like hiking, inline-skating, climbing or board game nights</li>
<li>Competitive salary, flexible working hours, work from home</li>
</ul>
<h2 id="overview-of-our-tech-stack">Overview of our tech stack</h2>
<p>Google Cloud, Kubernetes, Terraform, ArgoCD, Docker, Python, Typescript</p>


MLOps Engineer (all genders)

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