Subject Matter Expert – Quantative/Scientific/Corporate
Pubblicato il 27-09-2026 - LILT AI in Milano
About The Opportunity We are looking for experienced professionals to support a cutting‑edge AI benchmarking project focused on highly specific professional silos. Candidates should have demonstrable background or academic exposure in at least one of these verticals:
- Highly Technical / Quantitative: Software Engineering, Mathematics, Robotics.
- Scientific / Regulatory: Healthcare (clinical parameters), Natural Science (chemistry/physics datasets), Manufacturing (industrial systems, CAD, optimization).
- Corporate / Creative: Finance, Media & Content, Office & White Collar.
The ideal candidate is not a traditional translator. They are a Technical Subject Matter Expert (SME) / AI Engineer who has localized fluency in one of the target languages. They must be capable of understanding, refactoring, and verifying code execution within a sandboxed environment, while simultaneously possessing deep contextual domain knowledge.
What You’ll Deliver
- Design realistic scenarios in your target language or English grounded in operational contexts.
- Adapt structured evaluation rubrics.
- Review AI and human‑generated responses for factual accuracy, quality, cultural appropriateness, and operational realism.
- Contribute to “gold standard” solutions reflecting best practices across the target locale and domain.
Qualifications
- Native‑level proficiency in the target language with strong professional English skills.
- 5+ years of professional experience in the target domain.
- Background in one or more relevant positions within the domain.
- Strong understanding of domain workflows and environments.
LILT is an equal opportunity employer. We extend equal opportunity to all individuals without regard to an individual’s race, religion, color, national origin, ancestry, sex, sexual orientation, gender identity, age, physical or mental disability, medical condition, genetic characteristics, veteran or marital status, pregnancy, or any other classification protected by applicable