![Canadian National Railway](https://media.trabajo.org/img/noimg.jpg)
Specialist System Data Integration
3 days ago
At CN, we work together to move our company—and North America—forward. Be part of our Information & Technology (I&T) team, a critical piece of the engine that keeps us in motion. From enterprise architecture to operational technology, our teams use the agile methodology to automate and digitize our railroad ensuring our operations run optimally and safely and our employees can focus on value-added tasks. You will be able to develop your skills and career in our close-knit, safety-focused culture working together as ONE TEAM. The careers we offer are meaningful because the work we do matters. Join us
JOB SUMMARY
Clients can be from within CN’s I&T team or direct lines of business. The specialist must build a full-time automated service between systems in the cloud for the positive train control with the machine learning and AI. Be part of the system architecture for infrastructure as a code and Work CI\CD tool with azure DevOPS. Be part of the technology exploration service to build the evolution of the existing services. Develop and maintain a virtualized and containerized infrastructure. Building test code, new design and optimisation monitoring tool. Be part of the DevOPS team and lead after action review for operation support.
***MAIN RESPONSIBILITIES**
- Identify Models to be used and improve model accuracy
- Participate in the product definition, especially around the aspect of AI, machine learning, to translate complex business requirement into concrete technical solution.
- Create new optimisation for Infra monitoring with integration with third party or internal script(s).
- Use the data in the log management for pattern recognition
- Develop cloud design pattern for availability, data management, design and implementation, management and monitoring.
- Build the structure for process and documentation
- Be able to build solution with the Azure, Google cloud platform and DevOps marketplace.
- Evolve and build best practice materials
- Build workshops and labs about cloud technologies, cloud operations, containers, orchestrators and microservices.
- Be the technical leader for the system integration dev ops
***MINIMUM REQUIREMENTS**
- Minimum of 10 years of experience.
- Computer Science or Engineering degree
- Strong knowledge in cloud computing
- Strong familiarity with CNN for objects detection, segmentation and classification.
- Experience with Tensorflow, Keras, Spark, Opencv, Pytorch, etc
- Experience with Natural language processing, text understanding, classification, pattern recognition, recommendation systems, targeting systems, ranking systems or similar
- Strong knowledge of CI/CD tools (Jenkins, Gitlab CI, Github Actions, etc)
- Able to code in Python, Java.
- Knowledge of monitoring and logging for containers and orchestrators.
- Familiar with ISO30162 and IoT
***ASSETS**
- Master or Ph.D in Computer Science, AI, machine learning or related technical field.
- Strong knowledge in cloud computing (Azure, Google)
- Knowledge of networking, security and protocol
- Knowledge of python
- PTC and Rail industry experience
- IoT experience
- Devops Certification
- Azure certification (developing solution)
- Google certification
**About CN**
CN is a world-class transportation leader and trade-enabler. Essential to the economy, to the customers, and to the communities it serves, CN safely transports more than 300 million tons of natural resources, manufactured products, and finished goods throughout North America every year. As the only railroad connecting Canada’s Eastern and Western coasts with the Southern tip of the U.S. through a 19,500 mile rail network, CN and its affiliates have been contributing to community prosperity and sustainable trade since 1919. CN is committed to programs supporting social responsibility and environmental stewardship. At CN, we work as ONE TEAM, focused on safety, sustainability and our customers, providing operational and supply chain excellence to deliver results.
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