About the Company
Domyn is a company specializing in the research and development of Responsible AI for regulated industries, including financial services, government, and heavy industry. It supports enterprises with proprietary, fully governable solutions based on a composable AI architecture — including LLMs, AI agents, and one of the world’s largest supercomputers.
At the core of Domyn’s product offer is a chip-to-frontend architecture that allows organizations to control the entire AI stack — from hardware to application — ensuring isolation, security, and governance throughout the AI lifecycle.
Its foundational LLMs, Domyn Large and Domyn Small, are designed for advanced reasoning and optimized to understand each business’s specific language, logic, and context. Provided under an open-enterprise license, these models can be fully transferred and owned by clients.
Once deployed, they enable customizable agents that operate on proprietary data to solve complex, domain-specific problems. All solutions are managed via a unified platform with native tools for access management, traceability, and security.
Powering it all, Colosseum — a supercomputer in development using NVIDIA Grace Blackwell Superchips — will train next-gen models exceeding 1T parameters.
Domyn partners with Microsoft, NVIDIA, and G42. Clients include Allianz, Intesa Sanpaolo, and Fincantieri.
About the Role
Job Title: Machine Learning Engineer
Location: Remote (Italy)
Employment Type: Full-time
Department: Development
Overview
We’re looking for an extraordinary Machine Learning Engineer to join our Team in Milan. You’d work side-by-side with Developers, Designers, and Data Scientists to understand customers’ needs, proposing a range of insightful solutions and implementing and testing machine learning models as efficient services integrated into our product ecosystem. You’d also explore state-of-the-art Machine Learning research to improve current products and develop new ones. Other responsibilities will include continuously improving your scientific and engineering skills while helping others to improve theirs through mentoring and guiding them.
Requirements
What You Have:
- A Master’s Degree or PhD in quantitative fields, like Computer Science, Engineering, Stats, Math, or Physics
- At least 2 years of proven experience as a Machine Learning Engineer (or a PhD)
- Understanding of the fundamentals of statistics and machine learning, e.g., sampling theory, inference and interpretation, model validation, regression and classification techniques
What Would Be Nice To Have:
- Experience working closely with Product
- Experience developing scalable solutions to handle large and complex data
- Interest in MLOps best practices and tools, e.g., Kubeflow
- Experience with Graph DB technologies
- Proficiency in SQL
- Experience with LLM fine-tuning and deployment
- Proficiency in Object-Oriented Programming
- Experience with cloud resources, e.g., AWS, Google Cloud
- Familiarity with agile development
Who You Are
- Able to write and speak about complex technical concepts to broad audiences in a simplified format
- Strong team player, enthusiastic, curious, and talented at problem-solving, able to work independently and efficiently
- Interested in coaching, mentoring, and technical leadership
- Driven and not scared of facing new challenges
- Fluent in English and eager to work in a multicultural, international environment
Benefits
Perks:
- Learning Friday: A training budget for books, online courses, or other training materials.
- Smart Working: Save commuting time by working from home.
- Competitive salary based on experience, with an opportunity to receive company equity. The typical salary for this role ranges between €40,000 and €70,000, with compensation reviews based on experience and contributions.
