Machine Learning Engineer - Paid Internship With Base Compensation + Bonuses

Machine Learning Engineer Internship

This is a conversion‑oriented internship designed for candidates aiming for a full‑time ML engineering role.

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.

Our Team

• Machine Learning & Engineering: 14 people, including 4 Ph.D.s
• Business & Strategy: 3 people
• Leadership: 2 people

A lean, technical‑first team and we’re growing. We’re looking to add 5 new tech roles before the end of the year.

What You’ll Do?

Depending on your profile and interests, you could be placed on one of two flagship tracks:

• Track 1. AI for Financial Services : Work on Machine Learning solutions for one of the most data‑rich industries in the world. Problems you might tackle include prediction models, document analysis with ML, fine‑tuning LLMs for conversational data interfaces, and extracting actionable insights from large‑scale datasets.
• Track 2. Computer Vision for Pharma : Contribute to Computer Vision pipelines deployed in pharmaceutical environments, focusing on object tracking, behaviour understanding, and solving complex real‑world problems with nothing but a camera and a well‑trained model.

Both tracks involve close collaboration with senior engineers and direct exposure to enterprise clients. This is not a support role you’ll be expected to contribute from day one.

What You Will Learn?

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

Tech Stack

• Languages: Python, SQL
• ML Frameworks: PyTorch, XGBoost
• API Frameworks: FastAPI
• Databases: Snowflake, Postgres
• Cloud: Azure, AWS

How We Work?

• Communication: We run one short stand‑up every morning, align on daily priorities, and keep everything else in writing – project documentation on Linear and GitHub, async conversations on Slack with dedicated channels per team and project.
• Rhythm & Organisation: We work in weekly sprints so priorities are always clear. Every Friday we run a retrospective, an open conversation about what’s working and what isn’t.

Compensation

• Compensation: €830 gross/month (€5,000 gross total over 6 months)
• Contract type: Collaborazione Occasionale
• High non‑cash value (mentorship, fast promotion, relocation fully covered)
• Duration: 6 months, with a 1‑month trial period
• Relocation bonus: €3,000 gross, paid in three instalments of €1,000 each to support your move to Milan
• Monthly travel reimbursement: up to €370

Career Path

This internship is not a dead end – it’s the front door. We hire interns with an explicit intention of converting them into full‑time engineers. Most interns transition to a permanent contract within 3 to 6 months. The strongest performers make the jump in as little as 2 months. We don’t believe in making people wait if the fit is clear.

Localisation and Remote Work

This is a remote position – 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‑Friday: 8:30 – 17:30 CET
Lunch: 13:00 – 14:00 (flexible)

Selection Process

• Interview with CEO (15 min): Motivation, background knowledge and availability
• Interview with CTO or Senior Engineer (15 min): Company and role presentation, alignment on expectations
• Technical Interview (30–40 min): Technical discussion on ML principles and system design. No whiteboard coding or Leetcode‑style questions.

Total timeline: 3 to 4 weeks

Requirements

Mandatory

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

Benefits

• Equipment : You’ll hit the ground running with a MacBook Pro M5 14” yours to use from day one.
• Travel : Once a year, the whole team flies to Dublin for a 3‑day offsite at our HQ.