Applied AI Engineer - Energy Tech & Real-Time Trading

Tanqeeb

Dubai

On-site

AED 300,000 - 460,000

Full time

14 days+
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Benefits offered by this job

Competitive salary and equity
Biannual bonus
Fully expensed tech
Private health insurance
Breakfast and dinner allowance

Job summary

Fuse Energy is building an AI-driven energy platform in Dubai to make energy more affordable and accessible. You will design, develop and deploy AI-powered features that enhance consumer onboarding and personalized energy recommendations, while creating internal AI tools to boost productivity.

Applicants should have at least 3 years of engineering experience, strong Python skills, and hands-on work with AI/ML libraries, TensorFlow or PyTorch, and large-scale models.

Qualifications

  • Minimum 3 years of engineering experience.
  • Backend engineer with practical AI/ML experience.
  • Strong Python (or similar) with AI/ML libraries.
  • Experience deploying AI models to production.

Responsibilities

  • Design, develop and deploy AI-powered features for consumer experiences.
  • Build internal AI tools to improve company-wide productivity.
  • Collaborate with backend engineers and data scientists to integrate AI features.
  • Align AI models with real-time energy pricing and market conditions.
  • Improve models for energy trading and demand forecasting.
  • Stay updated with advances in applied AI and ML.

Skills

Backend engineering
Python programming
AI/ML libraries
LLMs/VLMs deployment
Cloud technologies
Containerisation
Data forecasting

Tools

TensorFlow
PyTorch

Job description

Fuse Energy is building an AI-driven energy platform in Dubai to make energy more affordable and accessible. You will design, develop and deploy AI-powered features that enhance consumer onboarding and personalized energy recommendations, while creating internal AI tools to boost productivity.

Applicants should have at least 3 years of engineering experience, strong Python skills, and hands-on work with AI/ML libraries, TensorFlow or PyTorch, and large-scale models.

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