Machine Learning Engineer
IKUE
Let's build the future together!
Ikue is a tech start-up with a clear purpose and vision - to providetelecommunications operators with a superior product to deliver superior
customer experiences.
We know that Customer data is at the heart of hyper personalisation and are
looking for the brightest, most inspiring engineers to deliver our product which
enables data to drive every decision, every communication, and every
customer interaction.
We are building a diverse team, all unified by a desire to unleash the data needed
by marketeers. Creativity is at the core of Ikue and is something we are looking to
further strengthen in 2022! There are no typical profiles, each and every team
member shares our vision and wants to be part of its success.
As a Machine Learning Engineer at Ikue you will:
- Design and construct Ikue's AI Studio in collaboration with Product owners and Data Scientists
- Design and build machine learning pipelines (model build, evaluation, deploy, monitoring)
- Integrate machine learning outputs into real-time and batch data pipelines
- Ensure machine learning and data pipelines are monitored, reliable and supportable (including expert support when required)
You will be rewarded with:
- You will become part of an international environment that embraces diversity and professionalism
- A dynamic and motivated team, with a good sense of humour
- Freedom to take responsibility, grow within the team and ALSO
- Working in a fast-forward company
- Remote work model
Requirements:
- BSc Computer Science or Engineering
- 3+ years working experience as a Machine Learning Engineer
- Advanced skills developing in Python, Spark , SQL
- Experience deploying and maintaining common machine learning models (e.g., binary classification, regression, clustering) in the cloud (AWS ECS and Sagemaker preferable)
- AWS Associate Developer certification (Machine Learning Speciality preferable)
- Excellent problem solving and analytical skills
- Strong communication and collaboration abilities
Vacancy posted more than 2 months ago
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