About Noos AI
Noos AI (Next-Gen Optimisation Operating System) is building the intelligence behind every inspection. Our mission is to eliminate data fragmentation in heavy industries like wind energy and aviation by fusing all inspection data - visual, thermal, LiDAR, vibration, and SCADA into one AI-driven decision layer. We're creating the world's first AI-powered industrial co-pilot , enabling faster, safer, and more reliable maintenance decisions.
Role Overview
We are seeking an AI Engineer Intern to help us design and deploy intelligence that powers Noos' inspection operating system and web platform. You'll build multi-modal AI models capable of interpreting visual, textual, and numerical data, generating insights, and supporting predictive and prescriptive decision-making. This role bridges core AI model development (for product operating software) and AI integration into our SaaS web application , ensuring that Noos feels intelligent, contextual, and adaptive across every user interaction.
Key Responsibilities
Model Development & Optimisation
- Develop and fine-tune multi-modal generative AI models for inspection data (image, vibration, SCADA, LiDAR, etc.).
- Build generative reasoning systems capable of correlating multi-sensor signals into actionable insights.
- Implement lightweight edge-deployable inference models for on-device and turbine-level intelligence.
- Research and integrate foundation models (vision-language, time-series, reinforcement learning) to enhance predictive reliability.
Platform Integration
Collaborate with the software and design teams to embed AI capabilities into Noos' web dashboard and APIs .Build prompt orchestration , context memory systems , and AI agents for inspection reporting and fault analysis.Design a feedback loop for real-time learning and continuous model improvement based on operator input.Data & Infrastructure
Work closely with the data engineering team to unify fragmented datasets into a common ontology.Contribute to a robust AI data pipeline from ingestion to labeling, training, and deployment.Optimize inference pipelines for latency, scalability, and energy efficiency in industrial environments.Requirements
Experience & Domain Background
Some experience developing and deploying AI / ML models (preferably in generative, multi-modal, or predictive domains).Has studied or worked in related industries , such as mechanical / electrical engineering, industrial automation, or aerospace systems with a clear understanding of real-world data sources (SCADA, vibration, imagery, etc.).Technical Skills
Strong foundation in Python , PyTorch , or TensorFlow .Experience with LLMs , Vision-Language Models (VLMs) , or Generative Time-Series Models .Proficiency in MLOps , API deployment , and cloud platforms (AWS / GCP / Azure) .Understanding of multi-modal fusion , embedding spaces , and transformer architectures .Experience integrating models into web applications (React / Node / Flask / FastAPI) .Familiarity with industrial or inspection data (imagery, vibration, LiDAR) is a strong plus.Soft Skills
A systems thinker who thrives on complexity and clarity.Strong collaboration mindset bridging AI, product, and design.Comfortable working in early-stage, fast-moving environments.Bonus
Previous Experience building autonomous agents or copilots .Contributions to open-source AI frameworks.Familiarity with industrial automation , wind energy , or aviation data systems.Previous work in industrial AI, wind energy, aviation, or predictive maintenance environments.Why Join Noos
Build frontier AI that impacts the physical world.Shape the future of intelligent inspection across industries.Work directly with a global, high-performing team combining robotics, AI, and design excellence.Be part of a company redefining industrial reliability from the ground up.Send us your applications at [HIDDEN TEXT]
Skills Required
Node, Tensorflow, React, Pytorch, MLops, Flask, FastAPI, Python