Internship - Machine Learning Engineer for AI Applications

About Us

We are a Machine Learning and Computer Vision startup founded in 2020, headquartered in Dublin, Ireland, with an AI Lab in Milan, Italy.

Our expertise spans Machine Learning and Generative AI for financial services and Computer Vision for life sciences.

At Gemmo AI, we build custom AI solutions that combine automation with human insight. We use a modular approach: first we explore the highest-impact opportunities, then we design and deploy tailored solutions, and finally we help improve and maintain them over time.

We believe in responsible, pragmatic AI: systems that integrate into real workflows, provide measurable value, and remain under your control.

About the Role

We’re looking for a Machine Learning Intern to help us build and integrate Machine Learning models into our clients’ cloud environments and production systems.

You will cover the entire ML pipeline, from data preparation to model training and deployment to the cloud.

What You’ll Do

• Build Machine Learning models for segmentation and classification with financial data
• Design, build, and maintain CRUD APIs to interact with users and serve the models
• Deploy, monitor, and maintain applications in AWS

Tech Stack

We use a mix of modern tools and languages. You’ll have the chance to explore and work with technologies like these:

• Languages: Python, Typescript, SQL
• ML Frameworks: PyTorch, XGBoost
• API Frameworks: FastAPI, Express.js
• Databases: Snowflake, Postgres
• Cloud: AWS
  

Remote Work & Schedule

This is a remote position, and you are free to work from anywhere in Italy.

However, if you fancy collaborating with other members of the team, you are welcome to join our Milan office (Via Zuretti 34, Milan).

Working hours:

• Monday–Thursday: 8:30 – 17:45 CET

• Friday: 8:30 – 16:30 CET

• Lunch: 13:00 – 14:00 (flexible)

We don’t do on-call rotations, your evenings and weekends are your own.

Recruiting Process

1. HR Screening (15 min): Company and role presentation, alignment on expectations.
2. Technical Interview (60 min): Technical discussion on ML principles and system design. No whiteboard coding or Leetcode-style questions.
3. Final interview with CEO (15 min): Final Q&A round, alignment on project.

Mandatory

• Master's degree in Computer Science, Data Science, Physics or other relevant STEM subjects.
• Experience with training custom ML models using PyTorch and XGBoost;
• Familiarity with API development;
• Good understanding of relational databases and experience with querying and managing data;
• Knowledge of version control systems (e.g., Git);
• B2+ English proficiency;

Nice to Have

• Experience with Typescript;
• Experience with interaction with LLMs (GPT, Claude, Gemini) via API calls;
• Experience with running Machine Learning inference jobs with PyTorch or ONNX;

• Monitor, camera and noise-cancelling headphones;
• Paid lunch and coffee breaks when in office;