Machine Learning Engineer Intern - Master’s

Key Skills

Algorithms, AWS, Data pipelines, Databricks, Machine learning techniques, Python Programming, PyTorch, SPARK Programming, Statistical modeling, TensorFlow

Job Description

Machine Learning Engineering Intern
Location: Boston, MA (Hybrid 2–3 days/week) or Remote (for qualified candidates)
Program Duration: 14 weeks (Internship) or 6 months (Co-op)
Compensation: Paid, Full-Time

Position Overview

We’re seeking a self-motivated and experienced Machine Learning Engineering Intern to join our growing team. This opportunity is ideal for someone pursuing or holding a Master’s degree in Computer Science, Data Science, or a related field, with prior industry experience in software engineering, ML engineering, or data engineering.

In this role, you'll work closely with ML engineers, data scientists, and application developers to accelerate experimentation, translate research into production-ready systems, and minimize technical debt. You’ll be expected to contribute independently and deliver high-quality solutions in a fast-paced, collaborative environment.

Key Responsibilities

• Partner with researchers to build, evaluate, and deploy production-grade ML models
• Refactor and improve existing pipelines for performance, scalability, and maintainability
• Design and implement robust ML workflows using Databricks (Spark/Delta Lake)
• Develop scalable data pipelines leveraging Spark and Delta Live Tables
• Support CI/CD, monitoring, and alerting workflows for deployed ML systems
• Integrate ML solutions into applications using AWS services such as S3, Lambda, ECS, and SageMaker
• Collaborate across engineering, product, and data teams to iterate on prototypes and drive production outcomes

Preferred Qualifications

• Pursuing or completed a Master’s in Computer Science, Data Science, or a related field
• 2+ years of relevant experience in machine learning, software, or data engineering
• Proficiency in Python and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, spaCy-NLP)
• Familiarity with Spark or distributed computing environments
• Experience building and managing ML pipelines and experimentation workflows
• Strong problem-solving and communication skills
• Ability to work independently and collaboratively

Bonus Experience (Nice to Have)

• Experience with healthcare data, EHR systems, or coding frameworks (ICD, SNOMED, CPT)
• Knowledge of HIPAA and other regulatory requirements
• ML Ops exposure: model serving, MLflow, monitoring, and deployment best practices
• Familiarity with DevOps tooling (e.g., Docker, Terraform)
• Hands-on experience with AWS and Databricks

What You’ll Gain at CodaMetrix

Our paid internship and co-op program is designed to provide meaningful experiences across all academic levels—from undergraduate through PhD. We are committed to helping students grow in the healthcare technology space through impactful projects, mentorship, and real-world exposure.

Program Highlights:

• High-impact, self-directed projects aligned to your interests
• Dedicated mentorship and feedback from an experienced manager
• Full participation in company-wide meetings and events
• Workshops and sessions on networking, resume writing, and career development
• Social and networking opportunities with peers and senior leadership
• Cohort-specific meetups for peer connection and collaboration

Location & Work Format

• Hybrid for Boston-based participants (2–3 days per week in-office)
• Remote options considered for candidates outside of commuting distance

Background Check Notice
All candidates must pass a background check as part of the offer process.