We are looking for an AI Engineer, to join our Mia-Platform group. Specifically, the person will work on our Mia-Care Team.
As an AI Engineer, you'll be at the core of what makes Mia-Care tick. Our platform uses LLMs to analyze medical device software, identify compliance gaps, and suggest actionable remediations. You'll own the intelligence layer that makes this possible, from model selection and adaptation to production deployment and cost optimization.
This isn't a role where you plug in an API and call it a day. You'll be shaping how AI works inside a highly specialized, high-stakes domain, where quality and reliability are non-negotiable.
Responsibilities
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Select, adapt, and evaluate pre-trained LLMs for domain-specific tasks, including prompt engineering, RAG pipeline design, and targeted fine-tuning where justified.
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Design and validate prompt pipelines using structured evaluation frameworks: ground-truth test sets, automated metrics, and regression suites, with documented acceptance criteria for production deployment.
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Own the full MLOps lifecycle: model versioning, monitoring, evaluation pipelines, and continuous improvement.
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Optimize for cost and scalability. You'll obsess over inference efficiency, latency, and making sure what you build can grow without burning the budget.
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Build AI pipelines that are reliable, observable, and production-grade from day one.
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Collaborate directly with product and domain experts to translate regulatory complexity into AI-solvable problems. No translation layer, no ticket queue.
How we work
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Full-stack AI mindset. You own your work end-to-end, from research and prototyping to deployment and monitoring. We value builders who take complete responsibility for their features without hand-off friction.
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Practical Engineering. We are a team of builders, not theorists. We prioritize writing clean, maintainable code and automating repetitive tasks to ensure our infrastructure remains robust and scalable.
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High ownership, low bureaucracy. We provide the autonomy to make critical technical decisions. In return, we expect a high level of accountability and a commitment to delivering excellence.
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Master’s Degree in Computer Science or Computer Engineering.
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0-2+ relevant years of experience.
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Proficiency in Python as the primary language. Rust is a plus for performance-critical inference components.
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Knowledge of LLM tooling: LangChain, the OpenAI and Anthropic ecosystems, and open-source model alternatives.
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Familiarity with MLOps tools and practices: Docker, GCP (Vertex AI, Cloud Run, GCS).
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Experience with LLM evaluation frameworks (such as RAGAS or DeepEval) and systematic prompt versioning practices.
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Familiarity with LLM production monitoring: output quality drift, latency, token cost tracking, and failure mode logging.
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Experience with retrieval-augmented generation (RAG) pipelines.
A competitive total-reward package
We offer a four-dimension package: Compensation (fixed and variable) + Benefits + Growth opportunities + an inspiring Culture.
Hybrid Workplace
We believe in work-life balance and know that smart working is one of the tools to achieve a more human-scale lifestyle. We recognize the value of teamwork, combining smart working with in-presence moments to be able to compare, exchange ideas, and move projects forward. We typically work 50% of our time from the office.
DE&I
As stated in our Manifesto we reject any form of discrimination and we strive every day to embrace diversity and to guarantee inclusion.
L&D and perks
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Training path and access to Mia-Platform hub with a vastity of training courses
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Team building and many surprising events
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Ticket restaurants
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Insurance coverage for medical expenses
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Corporate benefits platform with significant discounts on the purchase of different types of services (gyms, travel, technology, etc.)
