AI Engineer Intern

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