AI Engineer

Role Summary We are looking for a skilled AI Engineer to design, build, and deploy intelligent solutions using Large Language Models (LLMs), Natural Language Processing (NLP), and Computer Vision (CV). This role involves developing practical AI applications such as conversational agents, document analysis systems, image processing tools, and automation solutions. The ideal candidate is hands-on, product-driven, and enthusiastic about leveraging AI to solve real-world business challenges at scale. Key Responsibilities Model Development • Design, build, and optimize AI models across multiple domains, including: • NLP (text understanding, chatbots, document processing) • LLM-driven applications (RAG, agents) • Computer Vision (object detection, OCR, video analytics) • Fine-tune and customize pre-trained models for specific domain requirements • Explore and evaluate new architectures and techniques to enhance model performance Data Management • Gather, preprocess, and curate datasets for NLP and Computer Vision projects • Apply data augmentation strategies for text and image data • Maintain high data quality and relevance to support effective model training and evaluation Deployment & Integration • Deploy and integrate AI models into production environments • Monitor model performance and implement continuous improvement strategies • Optimize deployment pipelines for efficiency and scalability Monitoring & Optimization • Monitor model performance and identify areas for improvement • Implement monitoring and alerting systems to detect performance issues • Optimize model inference pipelines for latency and cost efficiency Collaboration • Partner with product, engineering, and business teams to deliver AI-powered solutions • Contribute to system design and architectural decisions • Promote knowledge sharing and best practices within the team Continuous Innovation • Keep abreast of the latest developments in LLMs, NLP, and Computer Vision • Assess, adopt, and integrate new tools, frameworks, and methodologies to drive innovation Requirements • Bachelor's degree in Computer Science, AI, Machine Learning, or a related field, or equivalent practical experience • At least 2 years of experience in AI/ML engineering, with a focus on NLP, LLMs, or Computer Vision • Proven hands-on experience designing, building, and deploying real-world AI systems • Experience with multimodal AI (text and image) • Familiarity with vector databases such as FAISS, Milvus, or Pinecone • Experience with real-time inference systems • Basic understanding of Docker and Kubernetes Technical Skills Core Skills • Proficient in Python with experience in deep learning frameworks (PyTorch, TensorFlow) • Strong understanding of machine learning, deep learning, neural networks, and model optimization AI / LLM / NLP • Hands-on experience with LLMs (GPT, LLaMA, Mistral), prompt engineering, fine-tuning, and RAG pipelines • Familiar with Hugging Face Transformers, LangChain, LlamaIndex; optional experience with spaCy/NLTK Computer Vision • Experience with image processing, CV models, and libraries such as OpenCV and torchvision • Familiar with object detection, classification, OCR, and segmentation tasks Deployment & MLOps • Skilled in model serving with FastAPI, NVIDIA Triton, or similar frameworks • Experience with monitoring/observability tools (Grafana, Prometheus) • Knowledge of deploying AI models on cloud platforms (AWS, GCP, Azure) What We Offer • Competitive Compensation: Enjoy a salary package tailored to your skills and experience, along with performance-based bonuses • Comprehensive Benefits: Visa processing and UAE mandated benefits • Work-Life Balance: Generous holidays and bonus policies • Top-Tier Equipment: Stay productive with the latest tools, including a MacBook and iPhone • Collaborative Culture: Immerse yourself in a dynamic, inclusive work environment that fosters growth • Employee Support: Bi-Annual travel/home visit reimbursements Show more Show less

Bachelor's degree in Computer Science, AI, Machine Learning, or a related field, or equivalent practical experience. At least 2 years of experience in AI/ML engineering, with a focus on NLP, LLMs, or Computer Vision. Proven hands-on experience designing, building, and deploying real-world AI systems. Experience with multimodal AI (text and image). Familiarity with vector databases such as FAISS, Milvus, or Pinecone. Experience with real-time inference systems. Basic understanding of Docker and Kubernetes.

Design, build, and optimize AI models across NLP, LLM-driven applications, and Computer Vision. Gather, preprocess, and curate datasets for NLP and CV projects; apply data augmentation; maintain data quality. Deploy and integrate AI models into production environments; monitor performance; optimize deployment pipelines for efficiency and scalability. Monitor model performance, implement monitoring/alerting, and optimize inference pipelines for latency and cost efficiency. Collaborate with product, engineering, and business teams; contribute to system design and architectural decisions; promote knowledge sharing and best practices. Stay updated with advancements in LLMs, NLP, and CV; assess and integrate new tools and methodologies.