MidFull TimeEN
Sproxil is a global brand protection & consumer engagement solutions provider specialized in the provision of cutting edge advanced technology to combat counterfeiting, product theft and adulteration; as well as providing a platform for consumer engagement. We are looking for a highly motivated Machine Learning / AI Engineer to join our team.
Key Responsibilities
Collect, clean, and organize data from various internal and external sources
Design and implement machine learning models for classification, regression, recommendation, NLP, computer vision, or other relevant tasks.
Build data pipelines for feature extraction, model training, and evaluation.
Optimize and fine-tune models for accuracy, latency, and scalability.
Collaborate with cross-functional teams to translate business requirements into AI solutions.
Deploy models into production using frameworks like TensorFlow Serving, TorchServe, or cloud-based tools.
Monitor and maintain model performance post-deployment, including retraining and versioning.
Document models, experiments, and workflows clearly and effectively.
Stay updated on the latest research and advancements in AI/ML.
Good understanding of prompt engineering
Good understanding of LangChain/LangGraph for the development of intelligent Agentic AI
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field.
2 years of experience in machine learning, deep learning, or AI-related roles.
Proficiency in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
Strong understanding of algorithms, statistics, and data structures.
Experience with data preprocessing and feature engineering for structured and unstructured data.
Familiarity with deploying models to production (e.g., using Docker, Flask, FastAPI, or cloud ML services).
Experience with version control (Git) and collaborative development practices
Competitive salary and benefits package
Collaborative and supportive work environment with an international team
Flexible work arrangement
