Architect - AI System
2 weeks ago
Our team has an immediate permanent opening for an Architect.
About the team
The Intelligent Complex Systems Team, currently a part of the Waterloo Research Centre, examines recent advancements in artificial intelligence (AI) and robotics to determine its potential for broader applications. This innovative team researches 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 updated with industry trends and advancements.
- Design and develop systems models and architectures for embodied AI or AI agent, utilizing exceptional problem-solving skills to overcome challenges and develop solutions.
- Proactively engage in research activities and identify new opportunities for research; present research findings and progress updates to team members and stakeholders; work with cross-functional teams to integrate them into practical applications.
- Investigate paradigms that can deliver a spectrum of embodied behaviors - from simulated characters to real robots/AI agents, and from short-horizon, low-level to long-horizon, high-level intelligence.
- Work cross-functionally to set the broader strategy and roadmap.
- Challenge the status quo, both technical and process.
- Mentor and guide junior team members to support their growth and development.
- Collaborate with external partners and research institutions to foster innovation and expand the reach of our research.
About the ideal candidate
- MS or PhD in Computer Science, Robotics, Artificial Intelligence, a relevant technical field, or equivalent practical experience;
- Proficiency in programming languages such as C/C++, Python, or similar;
- Excellent knowledge and hands-on experience with ML/DL, LLMs, multimodal foundation models, or large generative models, RAG, Multi AI Agent, AutoGen, CrewAI, prompt engineering;
- Outstanding engineering skills for rapid research prototyping, open-source release, or production development;
- Experience in building systems based on machine learning and/or deep learning methods, like motion planning, embodied AI, human-robot interaction, sim-to-real transfer, and dexterous manipulation;
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward;
- Experience in driving technical strategy and vision for engineering teams and organizations;
- Proven track record of achieving significant results and publications.
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