Our team has an immediate permanent opening for an Architect.
About the team :
The Intelligent Complex Systems Team, currently part of the Waterloo Research Centre, explores recent advancements in artificial intelligence (AI) and robotics to assess their potential for broader applications. This innovative team focuses on AI challenges such as matching human capabilities and ensuring the safety of collaborative AI systems.
About the job :
- Continuously learn and innovate in the field of intelligent autonomous systems to stay current with industry trends and advancements.
- Design and develop system models and architectures for embodied AI or AI agents, utilizing strong problem-solving skills to overcome challenges and develop solutions.
- Engage proactively in research activities, identify new research opportunities, present findings and progress to team members and stakeholders, and collaborate with cross-functional teams to translate research into practical applications.
- Investigate paradigms that can produce a range of embodied behaviors—from simulated characters to real robots/AI agents, spanning short-horizon, low-level to long-horizon, high-level intelligence.
- Work cross-functionally to define the broader strategy and roadmap.
- Challenge existing technical and process norms to foster innovation.
- Mentor and guide junior team members to support their professional growth.
- Collaborate with external partners and research institutions to expand research impact and foster innovation.
About the ideal candidate :
- MS or PhD in Computer Science, Robotics, Artificial Intelligence, or a related technical field, or equivalent practical experience.
- Proficiency in programming languages such as C / C++, Python, or similar.
- Strong knowledge and practical experience with ML / DL, LLMs, multimodal foundation models, large generative models, RAG, Multi AI Agent, AutoGen, CrewAI, prompt engineering.
- Excellent engineering skills for rapid prototyping, open-source contributions, or production development.
- Experience building systems based on machine learning and deep learning methods, including motion planning, embodied AI, human-robot interaction, sim-to-real transfer, and dexterous manipulation.
- Proven ability to solve complex problems, evaluate alternative solutions, and balance trade-offs to determine optimal paths forward.
- Experience leading technical strategy and vision within engineering teams and organizations.
- A track record of significant results and publications.
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