Location: Singapore, Singapore
In 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 established its presence in Singapore in 1973 to support the expansion of aerospace-related activities in the Asia-Pacific region. Throughout the last four decades, the company grew from strength to strength and is today involved in the primary businesses of Aerospace (including Air Traffic Management), Defence & Security, Ground Transportation and Digital Identity & Security. Thales today employs over 2,100 people in Singapore across all its business areas.
In 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.

The objective of this internship is to solve industry problems in aviation and defence using reinforcement learning trained agents. You will work on adapting existing reinforcement learning-trained models and optimising their performances in different environments. Through this internship, you will gain experience in the use of reinforcement learning agents in the fields of defence and air traffic management.

Responsibilities:

• Collaborate with internal users to determine the requirements of the trained model
  
• Create realistic environments to train reinforcement learning models
  
• Adapt existing models and generalise them for use in different environments
  
• Develop frameworks to automate the model training and deployment process
  
• Keep up with breakthroughs in the field of reinforcement learning
  

Key Requirements:

• Experience with deep learning libraries (e.g., Py Torch, Tensorflow)
  
• Interest or experience in reinforcement learning techniques
  
• Interest or experience with machine-learning operations for fast iteration
  
• Proficient in shell scripting and Python programming
  
• Strong team collaboration skills
  

Expected Outcomes:

• A working reinforcement learning model demonstrating adaptability in multiple environments
  
• Presentation of findings through various forms, including but not limited to live demonstrations, videos, and workshop presentations
  

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!