Machine Learning Engineer - Paid Internship With Base Compensation + Bonuses

Machine Learning Engineer Internship

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

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 include prediction models, document analysis with ML, fine‑tuning LLMs for conversational interfaces, and extracting actionable insights from large‑scale datasets.
• Track 2 – Computer Vision for Pharma
  Contribute to Computer Vision pipelines deployed in pharmaceutical environments, tackling object tracking, behavioural understanding, and complex real‑world problems using just 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: One short standup every morning, with all other interactions captured in writing via Linear, GitHub, and Slack.
• Rhythm & Organisation: Weekly sprints, daily priorities, and a Friday retrospective to discuss 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 the explicit intention of converting them into full‑time engineers. Here’s what that typically looks like: Internship → Full‑Time Conversion – Most interns transition to a permanent contract within 3 to 6 months. Top performers can jump in as little as 2 months, and we don’t want people to wait if the fit is clear.

• Starting Compensation (Full‑Time): RAL €33,000 gross, CCNL Metalmeccanico level C1
• Salary progression: +10% at each career level
• Salary reviews: annual
• Project bonuses: awarded on delivery and client impact
• Year‑end bonus: awarded for outstanding team performance

Remote Work & Schedule

This is a remote position; you are free to work from anywhere in Italy. If you wish to collaborate with 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): Discussion on ML principles and system design. No whiteboard coding or Leetcode‑style questions

Total timeline: 3 to 4 weeks

Requirements

• 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

• Experience with interaction with LLMs (GPT, Claude, Gemini) via API calls
• Experience with 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 off‑site at our HQ.