Über
Full‑time (32 hrs/week minimum), June 1 – Aug 25, 2026. Exact hours are flexible and coordinated with the technical team.
Location:
Primarily remote, with occasional in‑person work at our Baltimore office (3600 Clipper Mill Rd, STE 401).
Compensation:
$25/hour + $500 home office stipend at start of internship.
About the project Vectech builds AI‑powered tools that identify mosquitoes and ticks from images, helping public health organizations make faster, smarter decisions about vector control. Our computer vision models are deployed in the field, encountering new regions, species variants, and phenotypes, which can cause model performance to drift.
This internship focuses on understanding that drift. You will work with the computer vision team to develop analysis methods that track how geographic and genetic diversity affect model performance in the field and to identify early warning signs that a model needs retraining. This is real MLOps work on a deployed production system, not a toy dataset.
Responsibilities
Collaborate with product management to develop and maintain dashboards tracking product usage and performance.
Analyze data from deployed computer vision systems to generate insights and identify trends.
Create clean, intuitive visualizations for internal reporting and external communications.
Assist in preparing figures and data summaries for presentations, publications, or stakeholder meetings.
Help ensure data quality and consistency across different sources and platforms.
Respond to data requests with curiosity, efficiency, and appropriate skepticism.
Participate in team meetings, contribute to project planning, and ask great questions.
Make SQL queries, prepare datasets, and train computer vision models on various research problems.
Support development of improved modules in Vectech’s computer vision suite.
Required Experience / Skills
Proficiency in Python and familiarity with TensorFlow or PyTorch.
Hands‑on experience in computer vision, image processing, or machine learning (research, coursework, personal projects).
Exposure to Linux systems.
Cumulative GPA of 2.5 or above.
Readiness to learn fast and adapt.
Curiosity about public health and environmental science.
Preferred Experience / Skills
Experience with MLOps concepts (model monitoring, dataset drift, retraining pipelines).
Familiarity with SQL and data visualization tools.
Experience contributing to shared codebases (Git).
Prior experience analyzing real‑world deployed model performance.
Candidate Eligibility This position is funded through the Maryland Lighthouse Industries and AI Internship Program. Eligible candidates must meet one of the following:
Current graduate student (Master’s or PhD) enrolled at a Maryland institution of higher education.
Current undergraduate senior enrolled at a Maryland institution of higher education.
Maryland resident who is a current undergraduate senior or graduate student at an out‑of‑state institution.
Recent graduate (within 2 years of completing an Associate’s, Bachelor’s, Master’s, or PhD) who is a Maryland resident.
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Sprachkenntnisse
- English
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