Proximus
Job title:
AWS ML Engineer
Company
Proximus
Job description
Role descriptionAs a AWS Machine Learning engineer, you will play a key role in developing end-to-end solutions for machine learning use cases. By taking up a use case right from the start you will help business define and scope the problem, pick the right machine learning solution and technology as well as ensure implementation, integration and deployment of your solution to production. You will do so while ensuring that our internal governance processes and best practices are respected. You will also collaborate with other team members in knowledge sharing as well as continuously improving our way of working.Responsibilities
- Translate business requests into data requirements, extract the required structured and unstructured data from the Proximus data lake, data warehouse and other data sources (e.g. operational systems) and prepare large-scale datasets for modelling.
- Identify high-value use cases through data exploration and visualization.
- Develop predictive models using state-of-the-art machine learning and statistical methods.
- Pilot prototypes in production processes to demonstrate their value.
- Deploy prototypes to production, with support of IT, to obtain reliable, scalable systems.
- Present your results in a clear manner and discuss them with multi-functional project teams.
- Work in close collaboration with business experts (e.g. for requirement gathering, data source identification, data and process understanding, feature engineering, result validation, etc.), with IT (e.g. for ETL, deployment to production, etc.) and with other machine learning engineers in the team (e.g. for knowledge sharing).
Degree & Experience
- PhD or Master’s degree in a quantitative field (Artificial Intelligence, Computer Science, Engineering, Statistics, Mathematics, etc.)
- 3+ years of relevant work experience in a business environment
Technical skills
- Strong knowledge of state-of-the-art machine learning and statistical methods.
- Hands-on experience with Python and its machine learning ecosystem. Experience with deep learning (e.g. Tensorflow, PyTorch), big data (e.g. Spark, Hadoop) and real-time streaming is a plus.
- Hands-on experience with Cloud (AWS) & Data Bricks;
- Proven proficiency in the end-to-end machine learning project life cycle, including:
- Translating business requests into data requirements.
- Identifying high-value use cases through data exploration and visualization.
- Developing machine learning solutions (incl. feature engineering, model fitting, etc.).
- Proficiency in using Git for version control and collaborative development within a team environment.
- Understanding of software development best practices, including code reviews, testing and documentation.
- Deploying scalable machine learning applications to production.
- Any experience with following elements is a big plus:
- MLOps practices, e.g. orchestration with Airflow, Gitlab CI/CD, etc.
- Containerized deployment of ML products – e.g. docker, podman, Kubernetes
Attitudes/Behavior
- Passionate about machine learning and a constant learner
- Result-oriented and highly proficient in transforming data into actionable insights that create business value
- Proactivity with a strong sense of ownership over projects
- Excellent problem-solving skills and attention to detail
- Team player with strong communication and presentation skills
- Able to manage machine learning projects in an autonomous way and drive collaboration with domain experts, data engineers and other machine learning engineers
- Experience working with Agile methodologies, particularly Kanban, to effectively manage and deliver project tasks
- Knowledge in the field of telecommunications is a plus
Languages
- Fluent in English and preferably also Dutch and/or French.
Expected salary
Location
Brussel
Job date
Sat, 09 Nov 2024 05:12:55 GMT
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