Brief Job Description:

Researches and prototypes the capabilities that power Constructor’s education products — applying AI and quantum through an education lens to improve how people teach, learn, and do research, rather than pursuing AI or quantum science as an end in itself. Forms hypotheses, designs and runs experiments, interprets results, and turns validated findings into working code that feeds product and engineering pipelines. Works independently, sets its own research agenda within the broader product strategy, and produces high-quality work that moves the platform and its users forward. Works closely with research associates, ML engineers, and technical leadership to make sure the work has real-world impact across the AI software development project. Requires 7+ years of applied research experience — ideally in education technology or applied AI — with a track record of turning research into products that ship.

Mission:

Set and pursue a research agenda that produces results worth shipping — then make sure they land in the products and engineering pipelines that depend on them.

Education:

• PhD in Computer Science, Physics, Mathematics, or a related field — or equivalent applied research experience. A track record of impact through research that shipped into products, patents, or publications.

Duties and Responsibilities: 

• Set a research agenda aimed at real product and platform problems, within the broader strategy.
• Design and run rigorous experiments; interpret results and decide what to take forward.
• Turn validated findings into proof-of-concept code, drive it to production, and benchmark its impact in real products.
• Deliver results as working proof-of-concept code first; reports, publications, or patents follow only where they add value — never in place of running code.
• Mentor research associates, guide experimental direction, and partner with ML engineers to ship the work.

Qualifications and Experience:

• 7+ years of applied research or research-engineering experience — ideally in education technology or applied AI.
• Proven track record of research that reached production or had measurable real-world impact (publications/patents a strong plus).
• Deep expertise in experiment design, modelling, and result interpretation.
• Strong hands-on coding (Python, PyTorch) — ships runnable proof-of-concept code, not just designs; reproducible work via version control (GitLab) and experiment tracking (MLflow).
• Able to work autonomously and balance scientific rigour against shipping speed.

Nice to Have (Not Obligatory):

• Track record of moving research into production ML systems at speed.
• Experience with AI-for-education products, or a quantum computing / quantum machine learning background.
• History of mentoring researchers or leading a small research team.