Translation Empire PK is seeking an expert and highly motivated Deep Learning Specialist to focus on designing and deploying advanced deep learning models for image, text, and signal data — solving complex problems where traditional machine learning approaches fall short. This specialised role requires a Master’s or PhD in AI or Deep Learning, 3+ years of deep learning experience, strong proficiency in TensorFlow and PyTorch, and hands-on expertise in transfer learning, GANs, transformers, and LLM fine-tuning — contributing deep technical excellence to a growing AI-driven organisation in the UAE.
About This Deep Learning Specialist Opportunity
Company: Translation Empire PK — an AI and technology-driven organisation seeking deep learning expertise for advanced model development and deployment
Problem Domain: Image, text, and signal data — solving complex challenges where traditional machine learning methods cannot deliver adequate performance
Core Focus: Designing and optimising deep learning architectures, fine-tuning LLMs and CNNs, and deploying models to production environments
Salary: Market Competitive — for a PhD or Master’s level Deep Learning Specialist with 3+ years of proven expertise
Why This Deep Learning Specialist Role Stands Out
Advanced DL Architecture Scope: Design and optimise deep learning architectures across NLP, computer vision, and signal processing — pushing beyond conventional ML limitations
LLM & CNN Fine-Tuning: Apply fine-tuning techniques to Large Language Models and Convolutional Neural Networks — adapting foundation models to specific project requirements
Production Model Evaluation: Evaluate and improve deep learning model performance in real production environments — not just research or laboratory settings
Model Quality Engineering: Address overfitting, data imbalance, and model bias — building robust, generalizable deep learning systems that perform reliably in deployment
Position Overview
This Deep Learning Specialist at Translation Empire PK in the UAE designs and optimises deep learning architectures for image, text, and signal data use cases, fine-tunes Large Language Models (LLMs) and Convolutional Neural Networks (CNNs) based on project requirements, addresses challenging model quality issues including overfitting, data imbalance, and model bias, evaluates deployed deep learning models in production environments for reliability and performance, and shares deep learning best practices with engineering teams — applying advanced expertise in TensorFlow, PyTorch, transfer learning, GANs, and transformers to solve problems where traditional machine learning fails.
Why This Role Matters: As Deep Learning Specialist at Translation Empire PK in the UAE, you operate at the frontier of what AI can achieve — designing neural architectures that can understand images, language, and signals in ways that conventional machine learning simply cannot. Whether you are fine-tuning a transformer-based LLM for domain-specific text understanding, training a GAN to generate high-quality synthetic data, or building a CNN pipeline for production image analysis, your technical depth is the difference between an AI system that works in theory and one that delivers measurable value in production at real scale.
Key Responsibilities
Deep Learning Architecture Design & Optimisation
- Design and optimise deep learning architectures for image, text, and signal data use cases — creating models that solve problems where traditional machine learning approaches fail
- Fine-tune Large Language Models (LLMs) and Convolutional Neural Networks (CNNs) based on specific project requirements and domain data characteristics
- Apply transfer learning techniques to adapt pre-trained foundation models to new domains with limited labelled data
- Research, select, and implement the most appropriate deep learning architecture — CNN, RNN, transformer, GAN, or hybrid — for each specific AI challenge
Model Quality, Evaluation & Production Deployment
- Address core deep learning model quality challenges — including overfitting, data imbalance, and model bias — using proven regularisation, augmentation, and resampling techniques
- Evaluate deep learning models in production environments — measuring performance, reliability, and stability against real-world data distributions
- Design and implement rigorous model evaluation frameworks — validation strategies, metrics selection, and performance benchmarking against relevant baselines
- Develop solutions for model reliability and generalisation across diverse, complex, and imperfect production datasets
Best Practice Sharing & Team Collaboration
- Share deep learning best practices, technical insights, and engineering standards with the broader engineering team
- Contribute to building organisational deep learning capability — upskilling colleagues on DL methods, frameworks, and production deployment approaches
- Collaborate with engineering teams to integrate deep learning solutions into product and production systems
Qualifications & Experience Requirements
Essential Requirements
- Master’s or PhD in Artificial Intelligence, Deep Learning, Machine Learning, Computer Science, or a closely related quantitative field
- Minimum 3+ years of dedicated deep learning experience — designing, training, fine-tuning, and deploying production DL models
- Strong grasp of deep learning frameworks — TensorFlow and PyTorch — with hands-on model building, training, and optimisation experience
- Experience with transfer learning, Generative Adversarial Networks (GANs), and transformer architectures
- Strong understanding of deep learning model evaluation, validation, and production performance monitoring
- Ability to address overfitting, class imbalance, and bias issues in deep learning systems systematically
Preferred Qualifications
- Relevant AI or deep learning certifications — preferred
- Experience with LLM fine-tuning and prompt-based adaptation for domain-specific NLP tasks
- Experience deploying deep learning models in production environments — not just research prototypes
- Experience with computer vision, NLP, or signal processing deep learning applications
About Translation Empire PK — Where Deep Learning Meets Real Impact
Translation Empire PK is an AI and technology organisation seeking exceptional deep learning expertise to tackle the most technically demanding challenges in image, text, and signal processing — building and deploying advanced neural architectures that go far beyond what conventional machine learning can achieve. With a focus on LLM fine-tuning, CNN optimisation, GAN development, and transformer-based solutions, Translation Empire PK offers deep learning specialists in the UAE the opportunity to work on genuinely hard AI problems — with a competitive market salary and a collaborative engineering environment that values technical excellence and knowledge sharing.
Career Excellence: Design and deploy frontier deep learning models — LLMs, CNNs, GANs, and transformers — solving AI challenges where traditional ML falls short in the UAE.
Who Should Apply?
- PhD & Master’s Deep Learning Researchers: With 3+ years of applied deep learning experience — architecture design, TensorFlow/PyTorch model training, and production deployment
- LLM Fine-Tuning Specialists: With hands-on experience fine-tuning transformer-based Large Language Models for domain-specific NLP or multimodal applications
- Computer Vision & CNN Engineers: With convolutional neural network architecture design and image/video model production deployment experience
- GAN & Generative AI Practitioners: With practical GAN training, evaluation, and application experience — synthetic data, image generation, or domain transfer
- UAE-Based Deep Learning Professionals: With Master’s or PhD credentials, deep TensorFlow/PyTorch expertise, and a passion for solving difficult AI problems at the technical frontier
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