Machine Learning Engineer Internship

About DentalScan

DentalScan is the medical AI division of ReplyQuick, one of the fastest-growing and most tractioned startups in the United States.

We develop supervised machine learning systems for intra-oral image analysis using smartphone-captured dental photos, focused on helping families in need, children in need, underserved communities, and people without access to immediate dental care.

We currently maintain a 50,000-image labeled dataset and are expanding toward 100,000 labeled images as part of our continuous retraining and improvement pipeline.

Our clinical categories include:

• Gum inflammation and gingivitis staging

• Plaque and calculus detection

• Recession classification

• Orthodontic tooth movement tracking

• Implant and crown monitoring

• General intra-oral diagnostic classifications

This internship is reserved for highly talented developers who are passionate about medical image analysis, supervised learning, and building meaningful technology with real-world impact.

We are specifically working on an advanced machine learning module and a fully automated retraining pipeline deployed through AWS. Because of this, strong AWS experience is mandatory. Applicants without AWS experience or certification should not apply.

Role Overview

As a Machine Learning Developer at DentalScan, you will work directly on our supervised ML models, dataset ingestion workflow, augmentation pipeline, retraining system, and clinical validation processes.

You must bring prior experience in ML development, a strong foundation in computer vision, and a genuine passion for using your skills to help build one of the most meaningful medical AI products in the U.S.

This is a 12-week, unpaid internship with the possibility of transitioning into a paid full-time ML position upon strong performance.

You must attend two daily meetings (10:30 AM PST and 2:30 PM PST) and commit 20–25 hours per week consistently.

Because we receive a large number of applicants and fill positions extremely quickly (often within an hour), we will only consider candidates who have real experience, AWS proficiency, clear commitment availability, and a passion for impact-driven medical AI.

Responsibilities

• Develop and refine supervised ML models for intra-oral image classification

• Integrate and preprocess open-source production datasets

• Perform dataset cleaning, augmentation, balancing, and quality improvement

• Implement continuous retraining using dentist-corrected labels

• Work with AWS services as part of the ML pipeline (mandatory)

• Perform error analysis, evaluation, and validation across all categories

• Collaborate with backend engineers to deploy and maintain ML endpoints

• Maintain proper documentation, experiment tracking, and dataset versioning

• Participate in daily syncs and align with ML milestones

Required Qualifications

Only highly qualified and passionate applicants will be considered.

Clear AWS experience is required. Applicants without AWS experience will not be considered.

• Strong knowledge of Python and machine learning fundamentals

• Experience training deep learning image models (CNNs, classifiers, supervised learning)

• Experience with AWS (S3, EC2, Lambda, or SageMaker required). AWS certification strongly preferred.

• Prior exposure to data labeling, dataset QA, or annotation workflows

• Experience handling image datasets and preprocessing pipelines

• Proficiency with PyTorch or TensorFlow

• Excellent debugging, problem-solving, and analytical ability

• Genuine passion for medical AI and impact-driven work

• Commitment to 20–25 hours per week and required meetings

• Clear communication, reliability, and disciplined execution

This role is designed for individuals who are serious about developing production-level ML experience.

If you do not meet these requirements, please do not apply and allow space for other dedicated candidates.

What You Will Gain

• End-to-end experience building and deploying real medical AI systems

• Hands-on work with large supervised image datasets (50k–100k )

• Exposure to continuous-training pipelines and real dentist-labeled feedback loops

• Meaningful work impacting families, children, and underserved communities

• A professional reference letter and completion certificate upon internship completion

• Priority consideration for a paid full-time ML position based on performance

• Production-level experience inside one of the most rapidly advancing AI-driven medical startups in the U.S.

• Strong portfolio visibility and recognition across LinkedIn and the broader tech/AI community

Full-Time Opportunity Pathway

At the end of the 12-week internship, select candidates may be offered a transition into a paid full-time Machine Learning Developer role, depending on:

• internship performance and productivity

• reliability and communication

• how effectively they complete tasks and collaborate with the team

• the quality of their ML contributions and ownership

• the company's funding state and investment rounds

• meeting outcomes with investors and expansion of our capital resources

Only the highest-performing interns will be considered for this opportunity.

• IndustryTelecommunications

Employment Type

Internship