Machine Learning Engineer Intern

gemmo ai โ€ข Italy
Remote Relocation
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AI Summary

Gemmo AI is seeking a Machine Learning Engineer Intern to work on real production projects, contributing to AI solutions for financial services and computer vision for pharma. The ideal candidate will have experience with training custom ML models using PyTorch and XGBoost, familiarity with API development, and good understanding of relational databases.

Key Highlights
Conversion-oriented internship for a full-time ML engineering role
Work on real production projects, not toy datasets or internal tools
Close collaboration with senior engineers and direct exposure to enterprise clients
Key Responsibilities
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
Technical Skills Required
PyTorch XGBoost API development Relational databases Git SQL FastAPI Snowflake Postgres Azure
Benefits & Perks
โ‚ฌ830 gross/month
Relocation bonus: โ‚ฌ3,000 gross
Monthly travel reimbursement: up to โ‚ฌ370
Equipment: MacBook Pro M4 14"
Time Off: 20 days of paid holiday per year, 8 public holidays, 104 hours of additional permitted leave per year
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

Job Description


Machine Learning Engineer Intern โ†’ Full-Time Track

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

About Us

Do you think Artificial Intelligence is changing the world? So do we.

At Gemmo, we don't just build models: we help Fortune 200 companies like Novartis and Broadridge harness the power of AI to generate real, measurable impact.

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?

At Gemmo, interns work on real production projects not toy datasets or internal tools. 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?

You'll gain hands-on experience working alongside senior ML engineers on real production problems. Not simulations, not tutorials code that runs on enterprise systems.

  • 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

How We Work?

We're a small team, which means no bureaucracy, no silos, and no waiting three weeks for a decision. Everyone is expected to communicate clearly, move fast, and take ownership.

  • Communication We run two short standups every day a 15-minute morning sync to 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 morning we run a CEO retrospective, an open conversation about what's working and what isn't. Once a month, the whole company comes together for a Townhall to share progress, celebrate wins, and discuss where we're heading

Compensation

  • Compensation: โ‚ฌ830 gross/month (โ‚ฌ5,000 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: โ‚ฌ3,000 gross, paid in three instalments of โ‚ฌ1,000 each to support your move to Milan
  • Monthly travel reimbursement: up to โ‚ฌ370

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 โ†’ 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.

Starting Compensation (Full-Time)

  • RAL: โ‚ฌ33,000 gross CCNL level C1
  • Salary progression: +10% at each career level
  • Salary reviews: it happens every year
  • Project bonuses: awarded on delivery and client impact
  • Year-end bonus: a awarded for outstanding team performance

We're a fast-growing company. If you perform, you'll be rewarded quickly and visibly not in three years after your annual review cycle.

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. No trick questions, no whiteboard theatre.

  • Interview with CTO or Senior Engineer (15 min): Company and role presentation, alignment on expectations
  • Interview with CEO (15 min): Final Q&A round, alignment on project
  • Technical Interview (60 min): Technical discussion on ML principles and system design. No whiteboard coding or Leetcode-style questions

Total timeline: 3 to 4 weeks You'll receive feedback at every stage, no ghosting, no ambiguity.

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 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 brand new MacBook Pro M4 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 a mix of strategy, team building, and genuinely good craic.

Time Off: We believe rest is part of performing well. You'll have:

  • 20 days of paid holiday per year
  • 8 public holidays
  • 104 hours of additional permitted leave per year

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