Invisible Technologies
201 - 500 employees
Founded 2015
🤖 Artificial Intelligence
☁️ SaaS
🏢 Enterprise
🔥 Funding within the last year
💰 $100M Series unknown on 2025-10
Artificial Intelligence • SaaS • Enterprise
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.
SWE Infrastructure Specialist – JS/TS/Python, Freelance AI Trainer Project
Job not on LinkedIn
🕒 March 20
🌏 Anywhere in the World
💵 $80 - $150 / hour
⏳ Contract/Temporary
🟡 Mid-level
🟠 Senior
👷 Infrastructure Engineer
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Invisible Technologies
201 - 500 employees
Founded 2015
🤖 Artificial Intelligence
☁️ SaaS
🏢 Enterprise
🔥 Funding within the last year
💰 $100M Series unknown on 2025-10
Artificial Intelligence • SaaS • Enterprise
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.
📋 Description
• Converse with the model on infrastructure and platform engineering tasks using JavaScript, TypeScript, and Python • Verify architectural soundness and logical correctness • Assess code quality and testing strategies • Analyze performance bottlenecks and deployment risks • Capture reproducible failure cases • Suggest improvements to prompt design and evaluation metrics to strengthen model reasoning
🎯 Requirements
• Bachelor’s, master’s, or PhD in computer science, software engineering, or closely related technical field • Real-world experience in cloud platforms, infrastructure engineering, platform or DevOps roles, performance analysis, or QA practices • Clear technical communication and ability to clearly articulate system-level reasoning and tradeoffs
🏖️ Benefits
• Company-sponsored benefits do not apply
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