Research Associate

Responsibilities

• Scan recent research and turnrelevant techniques into prototypes the team can test fast.
• Design, implement, and runexperiments; analyse results and decide what's worth taking forward.
• Deliver each idea as workingproof-of-concept code - clean enough to hand to engineering, not just a writtensummary.
• Help integrate validatedresearch into product features and measure the impact.
• Work day to day with researchscientists, ML engineers, and product teams to move ideas from notebook toproduct.
• Qualifications &Experience
• 3+ years of applied research orresearch-engineering experience - ideally in education technology or appliedAI.
• Strong Python and PyTorch -able to produce runnable code others can extend, not just specs.
• Sound grasp of experimentdesign, statistics, and result analysis.
• Able to read recent papers andreproduce or adapt their methods into working code quickly.
• Reproducible, well-documentedwork using version control (GitLab) and experiment tracking (MLflow).

Requirements

• Experience taking researchprototypes into production or shipped product features.
• Publications, preprints, oropen-source contributions in AI or related areas.
• Exposure to AI-for-educationproducts, or to quantum computing frameworks.

Additional Information

Brief Job Description Contributes hands-on across the applied-research cycle behindConstructor's education products - surveying recent work, designing and runningexperiments, analysing results, and prototyping capabilities that apply AI andquantum through an education lens to improve how people teach, learn, and doresearch. Works closely with research scientists, engineering, and productteams, and helps turn early-stage ideas into working features that feed the AIsoftware development project. Requires 3+ years of research experience -ideally in education technology or applied AI - with a track record ofdelivering solid, hands-on output in a fast-paced, multidisciplinary setting. Mission Dothe hands-on experimental work that turns promising ideas into workingproof-of-concept code - quickly, and backed by evidence the product andengineering teams can build on. Education - Master's or PhD (ornear-completion) in Computer Science, Physics, Mathematics, or a related field- or equivalent applied research experience. Shipped research prototypes,open-source contributions, or publications all count.

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