Graduate AI/ML Engineer - UAE National

Location: Dubai, United Arab EmiratesIn fast changing markets, customers worldwide rely on Thales. Thales is a business where brilliant people from all over the world come together to share ideas and inspire each other. In aerospace, transportation, defence, security and space, our architects design innovative solutions that make our tomorrow's possible.Thales has built a presence in the United Arab Emirates for over 35 years, and today has over 300 employees. Thales in the UAE is part of our Middle East business that has 1,800 people across Egypt, Iraq, Kuwait, KSA, Lebanon, Oman, Pakistan, Qatar and UAE. Together we delivered technology for the Dubai metro, the longest driverless metro network in the world and a fare collection system that processes up to 250,000 transactions per day. We make UAE a safer place by providing secure electronic payment solutions, cyber security systems and communications as well as security systems for Dubai International Airport and air traffic management and navigation systems for Abu Dhabi’s airport.

Job Objective

We are seeking a talented and enthusiastic AI/ML professional to join our team. This position 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 helping us define a solution to digitalize documents and develop a system capable of predicting qualifications based on database analysis.

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 the digital documents to make predictions about qualifications.
• Perform data preprocessing and cleaning to ensure high-quality input for the 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.

Qualification, Certification & Educational Requirements

• 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.

Hse Responsibilities*

• Ensure both your own safety and the safety of others at all times.
• Maintain an active role in achieving the objectives and adhering to the HSE Thales Policy
• Comply with local HSE laws and legislation.
• To use safety equipment (including PPE) as required and intended.
• Lead by example and actively encourage departments to look at ways to conserve water & energy, minimise the generation of waste, and encourage recycling.
• Every one within Thales has the right to stop work if they believe that their activities may affect their health and safety or that of others. In this circumstance, such conditions must be reported immediately to their line manager and the HSE department.

At Thales we provide CAREERS and not only jobs. With Thales employing 80,000 employees in 68 countries our mobility policy enables thousands of employees each year to develop their careers at home and abroad, in their existing areas of expertise or by branching out into new fields. Together we believe that embracing flexibility is a smarter way of working. Great journeys start here, apply now!