Job Purpose:
This position is central to the research, development, and deployment of machine learning and AI systems across multiple industry-focused projects, ranging from predictive maintenance in factories to smart scheduling in restaurants or adaptive content generation in digital media. The AI Specialist will build intelligent systems that solve real-world problems by working closely with product managers, developers, and domain experts. The ideal candidate combines deep technical knowledge with a practical approach to deploying scalable, ethical, and efficient AI solutions.
Key Responsibilities:
- Design, develop, and deploy machine learning models and AI solutions tailored to specific industry needs.
- Collaborate with technical and domain teams to define data requirements and solution architecture.
- Fine-tune models using structured and unstructured data, including time-series, images, audio, or text.
- Integrate AI systems into broader application ecosystems through APIs or cloud services.
- Monitor AI model performance and continuously improve based on real-world feedback and evaluation.
- Ensure AI systems comply with ethical, regulatory, and safety standards relevant to the target sector.
Requirements:
- Proven experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience working with data pipelines and tools (e.g., pandas, SQL, Airflow).
- Strong understanding of AI principles such as NLP, computer vision, time-series analysis, or recommendation systems.
- Ability to adapt AI methodologies to practical constraints and business goals.
- Familiarity with deployment strategies (e.g., Docker, REST APIs, cloud ML services).
- Knowledge of responsible AI, model interpretability, and data governance.
Qualifications:
- Bachelor’s or Master’s degree in Artificial Intelligence, Computer Science, Data Science, or a related field.
- Track record of delivering AI projects or prototypes, preferably in applied industry settings.
- Strong analytical and communication skills; able to explain complex models to non-technical stakeholders.
- Experience with edge AI, reinforcement learning, or generative models is a plus.