Machine Learning Engineer
Location: Avenue du Bourget, 1140 Evere
Your mission:
As a collaborator in the Machine Learning team, you ensure the different predictive models and algorithms are running qualitatively and on time in the production environment also called the model factory. The mission of the machine learning engineer is key because this role makes the bridge between the products delivered by the Data Science team and the usage of the business.
The machine learning engineer will also cover some more technical missions such as web scraping and POCs concerning AI & Generative AI (in order to ensure a move to production for those POCs).
The Machine Learning team is responsible for the quality of the models and, consequently, the value created by the models that will be used by all internal clients.
As Machine Learning Engineer, you will:
1. Deploy large scale machine learning models and other scripts into production environments (in cloud and on-premise environments).
2. Review, optimize and simplify the code to ensure quality and reusability.
3. Monitor the quality of input variables and the performances of the models’ outputs.
4. Contribute to parts of the ML pipeline, such as data preprocessing, feature selection, and model evaluation.
5. Collaborate with data scientists, software engineers, and product teams to integrate models into production.
6. Monitor model performance and update models as needed.
7. Solve well-defined machine learning problems and may work on smaller projects or parts of larger projects.
8. Apply existing algorithms and techniques to specific business problems.
Specific expertise:
1. Expert understanding of git, experience with CI/CD pipelines.
2. Proficiency in Python and solid knowledge of at least one deep learning framework such as TensorFlow / Keras or PyTorch is a must.
3. Good knowledge of computational infrastructure.
4. Basic knowledge of Terraform.
5. Knowledge of machine learning techniques, general deep learning, predictive modelling, and Generative AI to challenge the inputs and outputs produced by the Data Science team.
6. Understanding of Google Cloud Platform, ML Ops principles, and software development tools/best practices.
7. Expertise in Data Ingestion/Processing and Modelling: able to express complex data needs and understand data quality-cleansing processes & methods.
8. Extensive Corporate Data Knowledge: aware of critical company business processes and underlying data, able to challenge data quality.
9. Fluency in SQL for writing efficient queries on large datasets.
10. Good knowledge of the Linux operating system.
11. Ability to write robust code in Python, R, and Java.
12. Good to have: knowledge of networking, multiprocessing, parallel computing, and real-time computations.
13. Ability to challenge the inputs and outputs of AI and Gen AI products as well as the way they were built.
Your profile:
1. Master’s degree in a related field (e.g., Computer Science, Data Science, Mathematics) or equivalent work experience with 2-5 years of experience in machine learning or related fields.
2. Proficient in key machine learning tools and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
3. Analytical thinking and self-learning spirit.
4. Strong programming and data analytics skills.
5. Able to work and collaborate transversally.
6. Good communication and presentation skills.
7. Collaboration skills with other data scientists, data engineers, and other teams.
8. Capacity to influence and engage, assertiveness, and being diplomatic.
9. Customer-oriented and pragmatic.
10. Stress resistant.
11. Fluent in English and fluent in French or Dutch.
Apply
Company:
Orange
Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):
Senior (5+ years of experience)
Tagged as: Belgium, Industry, Machine Learning, NLP
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