Micro-Intern: Research Assistant (IAP - Alumni Host)
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What you'll do
- Visit fashion retail stores (mostly in Boston area) to run experiments and collect high-quality datasets for evaluating our product
- Develop scripts to process and analyze large datasets
- Optimize machine learning models and processing pipelines for cost and efficiency
- Improve the accuracy of the outputs of our production models.
- Improve data collection tools to make them more automated, reliable, and easier to use
What they're looking for
- Strong Coder (Python): You can write software to solve problems effectively, whether it’s wrangling data, generating analytical reports, or optimizing parts of pipelines.
- Independent, High-Ownership: You are able to take a task, break it down, solve it with minimal oversight. You make sure work is completed, even if you hit roadblocks.
- Fast, Driven Learner: You like digging deep into unfamiliar territory, and you quickly pick up new skills along the way.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Micro-Intern: Software Engineer (IAP - Alumni Host)
Location: On-site; Boston/Cambridge, MA;
Dates: Full-Time; January 4, 2027 - January 29, 2027
Compensation: $20-25/hr
About the Company
Cartesian is building spatial intelligence for indoor environments to drive operational efficiency.
We’re tackling one of the biggest challenges in the $35T global retail industry: in-store inventory visibility. Our platform delivers accurate indoor positioning and actionable product location insights, helping retailers streamline operations, optimize workflows, and reduce inefficiencies. By fusing wireless signals and mobile computer vision, we provide a uniquely scalable and infrastructure-free solution already deployed by international fashion brands.
Founded by an MIT engineering professor and alum behind the award-winning, patented core technologies, Cartesian spun out in 2023. Originally backed by the prestigious SBIR Award from the US National Science Foundation, we've bootstrapped to a live product that's now deployed in over a dozen countries and have been aggressively scaling in the market.
About the Role
We’re looking for a highly motivated, product-oriented Machine Learning Scientist to join our core R&D team at a pivotal moment in our growth. You'll have a direct impact on key positioning algorithms & models, take ownership of new features, and help shape the technical roadmap of a category-defining product. We move fast, care deeply about quality, and value people who take initiative and crave real-world impact.
You’ll be joining us in-person in the heart of Kendall Square, Cambridge, next to MIT and the Charles River.
What You’ll Do
At the beginning of your IAP, we will define a specific project you will have ownership and responsibility for during the internship. This will require learning extremely fast, operating with ambiguity, and iterating on feedback each week. The project will likely combine many of the following:
- Visit fashion retail stores (mostly in Boston area) to run experiments and collect high-quality datasets for evaluating our product
- Develop scripts to process and analyze large datasets
- Optimize machine learning models and processing pipelines for cost and efficiency
- Improve the accuracy of the outputs of our production models.
- Improve data collection tools to make them more automated, reliable, and easier to use
About You
- Strong Coder (Python): You can write software to solve problems effectively, whether it’s wrangling data, generating analytical reports, or optimizing parts of pipelines.
- Independent, High-Ownership: You are able to take a task, break it down, solve it with minimal oversight. You make sure work is completed, even if you hit roadblocks.
- Fast, Driven Learner: You like digging deep into unfamiliar territory, and you quickly pick up new skills along the way.
Interview Process
- Screen (15 min): Sync on the role and your interests.
- Project Discussion (45 min): Show us something cool you’ve built. Explain your decisions, and what you learned.
- Coding (45 min)
- Offer
Company
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