Environment Specialist, Fluent in French β Freelance AI Trainer
Switzerland β Remote, remote, mid, contract, USD 8β65 / hour
seen 4d ago
- English
- Renewable resource management
- French
- Water quality monitoring
- Life cycle analysis
- Carbon accounting
- Environmental remediation
- Air quality monitoring
- Circular economy principles
- Environmental justice
About the role
Job not on LinkedIn
π Yesterday
π¨π Switzerland β Remote
π΅ $8 - $65 / hour
β³ Contract/Temporary
π‘ Mid-level
π Senior π€ Artificial Intelligence
π» Ghost score 0%
What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.
π£οΈπ«π· French Required
Where this job comes from
π’Posted on Invisible Technologies's careers page, not through a job board
πFirst seen by Remote Rocketship Yesterday
β Still open on Invisible Technologies's site. Checked 27 minutes ago.
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Invisible Technologies
Website LinkedIn All Job Openings
201 - 500 employees
Founded 2015
πΌ Consulting
π₯ Healthcare
π¦ Logistics
π° $100M Series unknown on 2025-10
Consulting β’ Healthcare β’ Logistics
Invisible Technologies is an enterprise AI platform and services company that builds and deploys production-grade AI systems for large organizations. They combine a modular SaaS platform (data platform, process builder, agents, evaluations) with an expert human marketplace to train models, automate complex back-office workflows, power contact centers, provide computer vision and demand-forecasting solutions, and ensure ongoing evaluation and governance. Invisible works across sectors (finance, healthcare, public sector, sports, retail) to integrate AI into real operational systems and scale outcomes.
β’ Converse with the language model in English and French on real-world environmental scenarios and theoretical questions β’ Verify factual accuracy and logical consistency β’ Capture reproducible error traces β’ Document model failure modes β’ Suggest improvements to prompt engineering and evaluation metrics β’ Challenge advanced language models on environmental topics including carbon accounting, life cycle analysis, environmental remediation, water and air quality monitoring, renewable resource management, environmental justice, and circular economy principles β’ Help train AI for environmental education, regulatory compliance, and conservation efforts
Read from remoterocketship.com, last seen 4d ago.