Data / Machine Learning Engineer
Data / Machine Learning Engineer
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Job Description
Inetum is in the midst of a strategic project to develop our competences in the area of artificial intelligence and data. The aim is to create cutting-edge AI solutions and competences that will enrich our product and service offerings responding to the growing needs of our customers. The project includes the analysis of existing processes the identification of areas where AI can bring the greatest benefit and the implementation of innovative machine learning models. We use Microsoft Azure and Google Cloud Platform cloud technologies to ensure the scalability and efficiency of our solutions. By joining the team you will have a real impact on shaping the direction of AI within our company.
Main Tasks
- Design development and implementation of machine learning models and AI systems in cloud environments (Azure Google Cloud).
- Creating and maintaining data pipelines: from data extraction and cleaning to feature engineering and preparing data for modelling.
- Selection of appropriate ML algorithms and their implementation and optimisation in the context of specific business problems.
- Collaborating with Data Science Data Engineering and Software Development teams to integrate models into production systems.
- Monitoring model performance conducting A/B testing and updating models in response to changing data and requirements.
- Keeping abreast of the latest ML trends and technologies and proposing innovative solutions.
Qualifications :
Must have requirements
- Minimum of 2 years experience as a Machine Learning Engineer or related position.
- Proficiency in Python and experience with ML frameworks (e.g. TensorFlow PyTorch).
- Knowledge of mathematics and statistics including linear algebra differential calculus and probability.
- Experience of working with large datasets and their processing and analysis.
- Familiarity with cloud tools and platforms such as Azure Machine Learning or Google Vertex AI.
- Ability to work in a team and communicate with technical and non-technical stakeholders.
Nice to have
- Experience in the implementation and optimisation of NLP or CV models.
- Knowledge of MLOps principles and tools for automating and monitoring ML models.
- Experience working with Docker containers and orchestration using Kubernetes.
- Familiarity with data and model versioning tools such as DVC.
- Participation in open-source projects or publications in the field of machine learning.
- Cloud-related certifications (e.g. Azure AI Engineer Associate Google Professional Machine Learning Engineer).
Additional Information :
Hybrid work from one of our offices in Warsaw Katowice Lublin Pozna or Rzeszw.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
