Role :The Embedded Artificial Intelligence Architect (Technical Lead) is responsible for the architecture, documentation, implementation, and training of complex AI/ML models for ground systems and embedded platforms, including those hosted on MDA's AURORA™ software-defined satellites-enabling AI capabilities in space. The role will initially focus on ground-based development and validation, progressing to on-board deployment where it delivers clear mission value and ROI (e.g., network traffic prediction, anti-jamming mitigation, and cognitive radio applications). Initially, this position will serve as the single accountable architect for AI, with the goal of achieving an initial deployment this year or early next year.
Responsibilities :- Lead the design and delivery of embedded AI solutions for satellite systems.
- Provide technical leadership across the AI/ML lifecycle (concept, architecture, implementation, verification, and deployment), including mentoring and technical decision-making.
- Collaborate with AI/ML experts across MDA divisions to share best practices and accelerate development.
- Perform problem formulation and feasibility studies for AI/ML applications in telecommunication satellites.
- Define a phased roadmap from ground prototypes to on-board inference, prioritizing deployments based on mission impact, risk, and ROI.
- Refine requirements and select appropriate model architectures to meet mission needs within embedded compute, power, memory, and latency constraints.
- Develop and evaluate AI/ML approaches for network traffic prediction, anti-jamming mitigation, and cognitive radio functions, and translate results into deployable system capabilities.
- Assess and prototype suitable learning approaches-including offline training, online adaptation, and (where appropriate) reinforcement learning-while ensuring robustness and verifiability for operational use.
- Design and implement complex simulators (e.g., digital twins) to generate representative training data.
- Create, curate, and manage datasets used for training, validation, and testing.
- Define metrics and evaluate model performance, robustness, and resource utilization on target platforms.
- Author and maintain technical documentation (architecture, design, training, verification, and deployment).
- Partner with system engineers and software developers to integrate AI capabilities into the end-to-end solution.
Requirements :- Sc. in AI/ML, Computer Science, Computer Engineering, or a related field (or equivalent practical experience).
- 10 years experience in embedded software development.
- Hands-on experience deploying or prototyping ML models on embedded targets (e.g., Raspberry Pi 5, Versal/FPGA-class devices).
- Strong Python skills; experience with TensorFlow (embedded deployment) and/or PyTorch.
- Ability to write production-quality code in C/C++.
- Experience with version control and collaborative development workflows (e.g., Git).
- Ability to work independently, prioritize effectively, and operate with minimal supervision.
- Strong written and verbal communication skills in English and/or French. Works with Ontario head office staff, English-speaking customers, during the product development phases
- Strong interpersonal skills and the ability to work effectively in large, cross-functional teams.
- Disciplined, resourceful, and committed to high-quality engineering outcomes.
Nice to have- PhD in AI/ML, Computer Science or Computer Engineering
- Experience with networking concepts, protocols, and architectures (e.g., DVB-S2X, 5G NTN, IP routing, SDN).
- Knowledge of satellite communication standards (e.g., DVB-S2X).
- CUDA experience and/or GPU optimization for model training or inference.
- Experience with RF systems and signal processing fundamentals.
- Experience using Jira and Confluence (or similar tools) to manage work and documentation.
- Experience with embedded Linux.
- Experience with disciplined software development practices (code reviews, testing, CI/CD).
- Fluency in French. Works with Ontario head office staff, English-speaking customers, during the product development phases
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Special Considerations :Successful candidates must obtain and hold security clearance at the reliability status level, and pass security assessment for the Controlled Goods Program (CGP) and ITAR.
Benefits statement :MDA provides competitive compensation and benefits packages for its employees at all locations. As a team member of MDA, you and your qualified dependents are eligible to participate in a benefit plan that ensures a comprehensive level of protection through competitive health care including; extended healthcare and flexible drug plans, dental and vision benefits, disability income protection, life insurance, group retirement savings plans; and an employee and family assistance program.
