Software intern Job at Thales
Location: Toronto, Canada
Thales people architect solutions that support 85 million mainline and suburban passenger journeys, worldwide, every day. Our Rail Signalling and Communication systems are used on metro lines across major cities, and 72,000 kms of route, 52,000 trains per day in 16 countries are controlled by our Traffic Management Systems. Together We deployed the first-ever nationwide ticketing system which processes over 50 million ticketing transactions in 100 cities daily.
Thales provides world-leading Communications-Based Train Control (CBTC) and interlocking for mass rail transit applications globally. The Centre of Competence for Urban Rail Signalling is located right before you at mid-town Toronto. As the largest office in Canada, we house a department for every step of the Software Development Lifecycle (SDLC)! This includes Software, Hardware, Systems Design, Verification & Validation, Operations, etc. The supporting corporate shared services teams in Finance, Human Resources and IT is also located at the office. Our office space was designed to provide a sustainable, healthy workplace that expresses TRSS’s brand while increasing collaboration. Features include Greenguard furniture, EnergyStar appliances, low-emitting adhesives, sealants, and sliding glass doors on internal offices provide daylight and views to the outside. Come join the big Transport family, here in Toronto!
As a part of the research and technology (R&T) team, you bring your knowledge in robotics, computer vision, fusion algorithms, point cloud processing or machine learning to build, test and review next generation solutions for the transit market. You will be involved in research and development to create “proof-of-concept” products for the urban rail-signaling domain.
Key Job Functions:
- Participate in the analysis of complex, real-time, autonomous system use cases
- Understand the goal of a research project and support its execution
- Analyze lab and field test results
- Assist with multiple sensors and the latest software algorithms to control complex, safety critical systems
- Become a highly productive team member and team player
Key Skill Requirements:
The successful candidate should be working towards a degree (Bachelors, Masters) in Computer Science or Electronics/Computer/Electrical Engineering or closely related field; possess good written and oral communication skills.
- Must be able to commit 8 months to the program
- Must be in their 3rd or 4th year (or more) of schooling
- Software development experience in C++, Python
- Be familiar with minimum set of python libraries (numPy, pandas, scikit)
- Practical experience of object oriented techniques, concurrency, parallelism, multithreading, socket programming in a Linux environment
- Knowledge of modern software engineering practices, methods and tools
- Experienced GIT user required
- Knowledge of Docker and containerization
- Knowledge of python versions and virtual environments
- Familiarity with Linux command line
- Demonstrated ability to follow instructions to deliver a quality technical solution on-time
- Supervised / unsupervised learning, online learning, classic computer vision algorithms, feature extraction, state estimation
- Object detection, tracking, matching, SLAM
Preferred Skills and Experience
- Knowledge of main concepts in Machine Learning and Computer vision
- Experience with relational database such as SQL, PostgreSQL and python integration
- Experience with AGILE workflow, JIRA
- IDE experience with Clion & Pycharm
- Knowledge of C++ GPU programming, CUDA, Python GPU processing and Library usage
- Knowledge of point cloud processing
#LI-Hybrid
Thales is an equal opportunity employer which values diversity and inclusivity in the workplace. Thales is committed to providing accommodations in all parts of the interview process. Applicants selected for an interview who require accommodation are asked to advise accordingly upon the invitation for an interview. We will work with you to meet your needs. All accommodation information provided will be treated as confidential and used only for the purpose of providing an accessible candidate experience.
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