Machine Learning Engineer Intern

Machine Learning Engineer Positions

We have to fill multiple positions.

Depending on your previous work experience (years in the job market), qualification (Bachelor, Master, Ph.D., Post-doc) you might be offered two types of position.

You have :

1. ..no work experience, and a Master / Bachelor -> We offer you an Internship
2. ..at least 2 year of work experience OR a Ph.D. / Postdoc -> We offer you a Full-Time Position

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: 20 people, including 4 Ph.D.s
• Business & Strategy: 2 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: You'll 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: You'll contribute to Computer Vision pipelines deployed in pharmaceutical environments, think 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

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

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

How We Work?

We're a small team, everyone is expected to communicate clearly, move fast, and take ownership.

• Communication We run one short standup every morning align on daily priorities. Everything else lives 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 and nothing drags. Every Friday we run a retrospective, an open conversation about what's working and what isn't.

Compensation - Internships

• Compensation: €830 gross/month (€5,000 gross total over 6 months)
• Contract type: Convenzione Stage curriculare / extra-curriculare
• Relocation bonus: €3,000 gross, paid in three instalments of €1,000 each to support your move to Milan
• Food Allowance: €600
• Monthly travel reimbursement: up to €370 /month
• Equipment : Brand new apple M5 14inch

• High non-cash value (mentorship, fast promotion)
• Duration: 6 months, with a 1-month trial period

Career Path for Interns

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. 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.

Compensation Full-Time

• RAL: €33,000 gross, CCNL Metalmeccanico level C3
• Relocation Package: €3'000
• Food Allowance: €1'200
• Project bonuses: awarded on delivery and client impact
• Year-end bonus: a awarded  for outstanding team performance
• Salary progression: +10% at each career level 
• Salary reviews: it happens every year
• Equipment : Brand new apple M5 14inch

• Contract Type: Tempo Determinato
• Duration: 6 months, with a 1-month trial period

Career Path for Tempo Determinato

You do a great job in your first six months with us and we will offer you a Tempo Indeterminato before the end of your contract.

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–Friday: 8:30 – 17:30 CET
• Lunch: 13:00 – 14:00 (flexible)

Selection Process

We keep it fast, respectful, and transparent.

1. Interview with CEO (15 min): Motivation, Background knowledge and Availability
2. Interview with CTO or Senior Engineer (15 min): Company and role presentation, alignment on expectations.
3. 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

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

Travel: Once a year, the whole team flies to Dublin for a 3-day offsite at our HQ.

Offsite: We also invite once a year the company to a nice place