Description:
You are a research scientist specializing in construction. You will have experience with AI, Machine Learning, LLM. You are passionate about solving problems and building things. You are excited to collaborate with industry partners to build leading edge features in Autodesk products. You are a good communicator and comfortable working at the intersection of research & product. This role is ideal for a PhD student with a keen interest in advanced technology development and a passion for enhancing the experience for construction professionals.
The location of this role is in Toronto, hybrid.
Responsibilities
- Investigate cutting-edge hardware, software, and experiential solutions that can improve the way construction personas receive and act on insights
- Research and implement experiences to test new technologies and approaches to construction insights delivery, tailoring them to the specific needs and challenges faced on construction sites
- Assess the effectiveness of new tools and methods, analyzing their impact on worker performance and site operations to refine and enhance their utility
- Work closely with a team of researchers, developers, and external partners toward research, development, and testing of these solutions
- Lead the development and scaling of machine learning models at the intersection of research and product
- Writing robust, testable code that is well documented and easy to understand
- Analyze errors and provide solutions to problems that arise
- Present the results of your work to collaborators and leadership
Minimum Qualifications
- PhD in Computer Science, Data Science, Construction, Architecture, Civil Engineering, or a related field
- 3 to 5 years of AI research experience
- A solid understanding of underlying Machine Learning pipelines
- Strong analytical and problem-solving skills
- Creative, flexible, and enjoy working with new technology Experience in coding (C++, Python…)
- Experience with cloud services & architectures (AWS, Azure, etc.)
- Excellent written communication skills to document code, architectures, and experiments