Thales is seeking a talented and enthusiastic AI/ML professional to join our team. This full-time hybrid position, based in Dubai, is ideal for recent graduates or final year students in Computer Science or IT Engineering who are passionate about machine learning and artificial intelligence. The incumbent will play a key role in defining a solution to digitalize documents and developing a system capable of predicting qualifications based on database analysis.
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Roles & Responsibilities:
- Collaborate with senior officials to understand project requirements and goals.
- Assist in the development and implementation of a machine-learning model to process and digitalize various documents.
- Work on algorithms that analyze data from digital documents to make predictions about qualifications.
- Perform data preprocessing and cleaning to ensure high-quality input for machine learning models.
- Conduct experiments and evaluations to measure the effectiveness of different models and approaches.
- Document processes, methodologies, and findings for future reference and knowledge sharing.
- Present progress updates and findings to the team in a clear and concise manner.
Work Experience Requirements:
- Solid understanding of machine learning concepts and algorithms.
- Experience with programming languages such as Python, R, or Java.
- Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
- Knowledge of data preprocessing techniques and tools.
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
- Ability to learn quickly and adapt to new challenges.
Qualifications:
- Educational background in Computer Science, IT Engineering, or a related field.
Preferred Skills:
- Experience with natural language processing (NLP) and document digitalization.
- Understanding of database design and management.
- Familiarity with cloud services and deployment (AWS, Azure, GCP).
- Previous internship or project experience in AI/ML.
Language Requirements: Not specified.
