Kindly note only applications submitted via this Expression of Interest form will be considered for the opportunity. Please find the details for the role below.
Job Type: Internship
Commencement Date: ASAP
Duration of Placement: 6 months
Role Timings: 9:00 AM - 6:00 PM
Salary: AED 1,500
Languages: English
Minimum Qualification: Any PG/UG Course
Job Description:
We are looking for Trainee AI Engineer to join our team and gain hands-on experience in developing and deploying artificial intelligence and machine learning solutions. This role is ideal for fresh graduates or individuals passionate about data, algorithms, and automation. You will work closely with data scientists, software developers, and project teams to build intelligent systems that solve real-world problems using AI technologies.
Key Responsibilities:
- Assist in designing, developing, and deploying machine learning and AI models.
- Work with data scientists to clean, preprocess, and analyze large datasets.
- Support in training, testing, and evaluating ML models using frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Collaborate with developers to integrate AI models into web or mobile applications.
- Help in creating APIs and automation pipelines for model deployment.
- Research and experiment with new AI tools, models, and techniques.
- Document experiments, results, and workflows for team reference.
- Stay updated with the latest advancements in AI, ML, NLP, and data science.
Requirements:
- Basic understanding of machine learning, deep learning, and data analysis concepts.
- Proficiency in Python and familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
- Knowledge of SQL and data visualization tools (e.g., Matplotlib, Power BI) is a plus.
- Familiarity with APIs, cloud platforms (AWS, Azure, or Google Cloud), or model deployment frameworks is advantageous.
- Strong mathematical and analytical problem-solving skills.
- Ability to work collaboratively in a team and follow Agile methodologies.
- A degree in Computer Science, Data Science, Artificial Intelligence, or a related field is preferred.
- Internship experience, coursework, or personal projects in AI or ML will be an added advantage.
- Basic Knowledge of the below:
Track 1: Classic Machine Learning
Track 2: Natural Language Processing (NLP)
Track 3: Computer Vision
Track 4: Generative AI & RAG (Retrieval-Augmented Generation)