data and machine learning engineering that enable exceptional user experiences, efficiency gains and new business models. In simple terms, we tech the heck out of data.

Our employee promise (besides offering engaging customer assignments of course) includes the possibility to enjoy the company's success and to shape who we are and what we do, together. We believe in being open about how the business is boomin’ and how the choices we make affect the bottom line. Take a look at our site to get to know us better.]]> A Machine Learning Engineer at Recordly typically works in tight cooperation with very skilled colleagues and our customers within different assignments. Assignments vary and typically require hands-on work from time to time - meaning you may have to open up AWS/Azure/GCP Console and deploy some machine learning resources, or write some MLOps stuff or data pipelines when the Data Engineers are not around.

As we focus on creating actual business value by creating or utilising for example data and machine learning platforms, we value the following skills:

Technical skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with data and machine learning technologies such as
- Fluent with cloud infrastructure, especially the data side of the big three. We don’t expect you to be certified (we can help you with that), but work experience at least within one of the big three is needed.
- Python - Yeah. This is our main tool in development. Knowledge of other languages is considered an advantage. Of course.
- MLOps concepts and tool(s) - The most important part of your job is to build the capabilities to enable productive machine learning solutions. We believe that MLOps and other <Dev/Data>Ops methods are an important part of that.
- Basic knowledge of machine learning models - It’s important to make business value using various machine learning models. To ensure this, a basic understanding of how the models work is sufficient, but even more important is the interest in how the models are operated in a production environment.
- Understanding and/or experience with Data Lake infrastructure, Data Warehousing, and Data Analytics tools. By this we mean, that you know what other tools (MDM, Data Catalogs, Data Lineage tools etc.) are needed for a good data platform and have some experience with those.
Ability to understand and translate business requirements into data and machine learning technical requirements. And we truly mean this. We want to be the glue, bridge, sellotape - whatever you want to call it - between the IT and business department, so that they understand each other.

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Market level salary plus a motivating bonus model.
Wide healthcare and insurance policy. Dental care and massages naturally included.
Workout while you work (Weekly time for wellbeing).
Lunch and culture benefit.
Your own company credit card plus flexibility to use it for example for your home office.
And more!

Besides those, we promise you challenging customer assignments. Go check out the amazing work our data architects have done.]]>
Our recruitment process typically consists of two interview rounds during which you will meet your future colleagues and learn more about working at Recordly. We also prefer to discuss technical aspects of the job through your own experience, so a technical task may be part of the recruitment process.]]>

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Machine Learning Lover