M(achine) L(earning) engineer

Description

Our client encompasses two major transmission system operators (TSOs) in two European regions: one in Belgium and 50Hertz Transmission, one of the four German TSOs, in northeast Germany.
Both TSOs operate at the heart of the European electricity system as they provide vital links between the various electricity producers and their 30 million end users. The Group’s high voltage network, with its intricately meshed 18,600 km grid, transports the electricity generated by the producers to the distribution system operators and major industrial consumers. In addition, interconnectors with several neighboring countries allow electricity trade in wider European energy markets.

Mission

You will be a member of an agile team, comprising energy data scientists, ML Engineers, and citizen developers from the business who have developed their own data science solutions. You will focus on models in production, both by developing new models, and by moving ML models developed by our team’s data scientists into production in a cloud and on-premises environments, and owning responsibility for their continued performance in production. This will also involve developing a model-monitoring pipeline for the models, together with our lead ML engineer, and taking ownership for model re-training and continuous improvements. You won’t be alone on the team, but rather working closely with data scientists, data engineers, and our lead ML engineer who will be there to support you along the way.

Resonsibilities

Decide on the best deployment set-up for a given ML model.
Set up a model deployment, monitoring and re-training pipeline, in our cloud and on-prem ML-Ops environments.
Continuously monitor the model’s performance, and decide on a re-training schedule together with the business, based on their needs.
Communicate with other members of our cloud and data teams, as well as with data scientists and express needs in due time.
Communicate with business stakeholders about the quality of the model, learn about their needs, and keep them in the loop about any changes.
Work together with data engineers and software architects to integrate the model together with other software and data tools.

Skills / Requirements

At least 3 years of experience in data science and machine learning, with a particular focus on models in production.
Previous experience in data or software engineering is a plus.
Experience with Docker.
Experience with ML flow a plus.
Experience with Databricks a plus.
Experience mentoring and supporting junior data scientists a plus.
Experience deploying to cloud environments (Azure experience a plus).
Experience writing production code (test-driven development, working with/creating CI/CD pipelines).
BSc or MSc in Computer Science, engineering, informatics, or similar is a plus.
Fluent in English. Additional language skills in German, Dutch or French is a plus.
Creative, autonomous, empathic, team player and result driven.
Good communication skills.

Do you want to apply for this job ? Let us know and send your CV to hello@akindra.ro

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