Machine Learning Engineer

WE ARE LOOKING FOR Machine Learning Engineer

We are looking for a Machine Learning Engineer with expertise in the development and training of deep learning models. The ideal candidate will have a strong background in data collection, establishing data pipelines and conducting exploratory data analysis, particularly within the Azure ecosystem.

Your future colleagues are waiting for you to join our international team. Working with us is uncomplicated, there’s a good team spirit, low-hierarchy and nonexistent bureaucracy. Our way of working is flexible too, many of our team work remotely from home with visits to our office from time to time when needed. This role is equally challenging, and as such we offer a very good compensation.

Key Responsibilities

• Design, develop, and implement deep learning models for various applications.
• Collect, preprocess, and manage data from diverse sources to support model training.
• Build and maintain robust data pipelines using Azure Data Factory or similar tools.
• Conduct exploratory data analysis (EDA) to gain insights and identify trends that inform model development.
• Optimize model performance through algorithm selection, hyperparameter tuning, and validation.
• Utilize Azure Machine Learning services for model training, deployment, and monitoring.
  
  

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field; Master’s degree preferred.
• A minimum of [3–5] years of hands-on experience in developing and deploying deep learning models.
• Experience in developing and deploying deep learning models using frameworks like TensorFlow, Keras, or PyTorch.
• Strong proficiency in Python and data manipulation libraries (e.g., Pandas, NumPy).
• Extensive experience with Azure services, particularly Azure Machine Learning and Azure Data Factory.
• Familiarity with data visualization tools and techniques for EDA.
• Solid understanding of machine learning algorithms, AI concepts, and best practices in model optimization.
• Experience with version control systems, such as Git.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.