AI/Machine Learning Engineering Intern

Gecko Robotics•New York, NY

1d•$50 - $90•Onsite

About The Position

Gecko Robotics is seeking an AI/ML Engineering Intern to join our Engineering team in New York for Summer 2027. This is a full-time, onsite internship, Monday through Friday. Gecko collects some of the richest inspection data in the world: ultrasonic and other non-destructive testing (NDT) measurements from wall-climbing robots, paired with the documents, drawings, and operational records that describe the assets they inspect. You will work on a defined project that turns that data into decisions, building models and the systems around them that run reliably on real customer data. This is an engineering internship, not an analytics one. We build the systems that analyze the data, not just the analysis. Due to government program requirements, candidates must be authorized to work in the United States.

Requirements

Currently pursuing a bachelor’s, master’s, or doctoral degree in computer science, electrical engineering, applied mathematics, physics, or a related technical discipline, with an expected graduation date between December 2027 and May 2028.
Ability to work onsite in New York, Monday through Friday, for the full Summer 2027 internship.
Strong programming experience in Python, including writing well-structured, tested code beyond notebooks.
Coursework or project experience in machine learning, including training and evaluating models on real datasets.
Working understanding of linear algebra, probability, and statistics.
Working familiarity with Git or similar version control systems.
Strong written and verbal communication skills, including the ability to explain results, quantify uncertainty, and collaborate on ambiguous problems.
Ability to independently close knowledge gaps, stay organized, and learn from feedback.

Nice To Haves

Graduate-level coursework or research in machine learning, signal processing, or computer vision.
Experience taking a model beyond a notebook: building a pipeline, an API, or a tool around it.
Experience with LLM APIs, retrieval, information extraction, or document understanding.
Experience with time-series or sensor data, especially ultrasonic, acoustic, or other physical measurements.
Exposure to cloud infrastructure, preferably GCP, and to containers such as Docker.
Interest in industrial, defense, or infrastructure applications where reliability matters.

Responsibilities

Own a scoped machine learning project from problem framing through evaluation and integration, under the guidance of experienced engineers.
Build data pipelines in Python that clean, label, and structure NDT sensor data, documents, or operational records for model training and inference.
Train, evaluate, and iterate on models, and design evaluations that reflect how the output will be used in the field.
Integrate a model or LLM-based workflow into a service or tool that other engineers and Forward Deployment Engineers can use.
Investigate failure modes on messy, real-world data, document what you find, and recommend what to fix next.
Use version control, code review, testing, and experiment tracking to produce work others can reproduce and build on.
Present your project, results, and recommended next steps at the end of the internship.