Machine Learning Engineer ML engineering · Gothenburg, Stockholm - Sverige - Modulai

Modulai Sverige

för 3 veckor sedan

Beskrivning

MACHINE LEARNING ENGINEER

As a member of the ML-team you will be working with a broad range of problems with one common denominator – ML will be the key ingredient.

You will have to analyze the problem at hand, come up with a solution strategy and execute it. This typically entails gaining an in-depth understanding of the challenge, understanding the available data, and then re-formulating it as an ML problem. It requires openness, creativity, and an eagerness to learn new methodology and explore new terrains.

We approach these problems as a team, meaning that you will have to be able to clearly explain your reasoning and code in order to engage the rest of us.

NOTE:
Right now we are looking for ML Engineers with +2 years of experience with ML in production. To apply you need to have a work permit forSweden.

Our Stack

Python / R – standard open-source libraries
Scikit-learn and various specialized Python and R ML libraries
Deep learning frameworks such as Pytorch and Tensorflow/Keras
Cloud platforms such as GCP, AWS, and Azure
Relational database management systems
Distributed processing such as Apache Spark

Responsibilities

Analyzing and planning problems, solutions, and delivery
Preprocessing, feature engineering, and dataset creation
ML model development
Validation of results
Data pipelining and infrastructure development

Background & Skills

MSc or Ph.D. in a quantitative field
Excellent understanding of a broad set of ML algorithms and frameworks
A passion for lean, clean, and maintainable code
The desire to grow and to share insights with others
Experience from ML i production

Helpful knowledge

Deep learning frameworks and theory
Data pipelining and infrastructure
DevOps experience, CI/CD, Kubernetes

About Team Modulai
At Modulai we focus 100% on solving problems with machine learning (ML). We work in teamson a project basis. We work for clients,as part of the core team instartups where we have long-time engagementas well as building our own ML products.

Learning and teamwork are central to how we work. Everyone in the team is or will soon bea full-stack ML engineer capable of scoping and developingend-to-end ML solutions. You should be able to do end-to-end machine learning products by yourself but actually, never do it because we always work in teams. If there is data, we will do ML on it

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