AI Engineer

Accountabilities:

• Design, develop, and deploy machine learning and AI systems for real-world applications at scale.


• Build, customize, optimize, and maintain AI models for domain-specific use cases.


• Develop and maintain data mining, preprocessing, feature engineering, and data-labeling pipelines.


• Work with large datasets to prepare high-quality training and evaluation data.


• Apply machine learning techniques across areas such as large language models, natural language processing, computer vision, and other AI domains.


• Train, evaluate, optimize, and continuously improve machine learning models based on performance results.


• Design and maintain model deployment and MLOps pipelines to support reliable production environments.


• Deploy and serve models using cloud platforms and containerized environments.


• Use Docker, Git, and relevant MLOps tools as part of collaborative software development workflows.


• Analyze model performance, identify limitations, and implement opportunities for improvement.


• Communicate technical concepts, findings, and project progress clearly to non-technical stakeholders.

Requirements

• 2–5 years of hands-on experience building and deploying machine learning or AI models in production environments.


• Strong proficiency in Python.


• Practical experience with PyTorch and/or TensorFlow.


• Experience designing and architecting custom AI or machine learning models.


• Hands-on knowledge of LLMs, NLP, computer vision, or another relevant AI domain.


• Strong understanding of supervised and unsupervised learning, deep learning architectures, optimization techniques, and model evaluation metrics.


• Experience with data preprocessing, feature engineering, data mining, and data-labeling pipelines.


• Familiarity with MLOps and model deployment tools such as MLflow, Kubeflow, or SageMaker.


• Knowledge of cloud platforms and services used for model training and serving, such as AWS Lambda.


• Experience with Docker and containerized model deployment.


• Familiarity with Git and collaborative software development practices.


• Strong analytical, troubleshooting, and problem-solving abilities.


• Ability to explain complex technical concepts clearly to non-technical stakeholders.


• Curiosity-driven mindset, adaptability, and comfort working in an evolving environment.


• Ability to work independently while collaborating effectively with distributed teams.

• Salary of EUR 4,000.


• Full-time employment.


• Fully remote work arrangement.


• Opportunity to work on real-world AI and machine learning applications at scale.


• Exposure to LLMs, NLP, computer vision, MLOps, cloud technologies, and production AI systems.


• Opportunity to work with modern machine learning and software engineering tools and practices.


• International and remote working environment.

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