Machine Learning Engineer

Company Description Not Yet is an emerging technology company focused on building practical, data-driven solutions powered by machine learning and artificial intelligence. The organization values experimentation, iterative development, and measurable impact, creating an environment where technical talent can shape products from the ground up. Team members collaborate across disciplines to design systems that are reliable, scalable, and useful for real-world applications.

The company encourages continuous learning, knowledge sharing, and professional growth through challenging projects and modern tooling.

Joining Not

Yet offers the opportunity to influence the direction of its technology stack and contribute to foundational ML infrastructure.

Role Description The Machine Learning Engineer will design, implement, and deploy machine learning models and end-to-end pipelines for production use. Day-to-day responsibilities include collecting and preprocessing data, experimenting with model architectures, evaluating performance, and optimizing algorithms for scalability and reliability. The role involves close collaboration with product, data, and software teams to translate business objectives into technical solutions and to integrate models into existing systems and applications.

The engineer will also maintain documentation, monitor deployed models, and iterate based on feedback and performance metrics. This is a full-time, on-site role based in Batna, Algeria.

Qualifications

• Strong foundation in Computer Science with practical experience implementing Algorithms and data structures.
• Proficiency in Pattern Recognition and Neural Networks, including designing, training, and evaluating ML models.
• Solid understanding of Statistics for data analysis, model evaluation, and experiment design.
• Hands-on experience with modern ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and Python or similar languages.
• Experience building and deploying ML pipelines, including data preprocessing, feature engineering, and model serving.
• Familiarity with software engineering best practices, such as version control, testing, code reviews, and documentation.
• Ability to work collaboratively in cross-functional teams and communicate complex technical concepts clearly.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience.
• Experience with cloud platforms or containerization (e.g., Docker, Kubernetes) is a plus.
• Background in applied machine learning projects or relevant industry experience is highly beneficial.