Description
We are seeking a highly skilled Applied AI Engineer to join our innovative team. In this role, you will be instrumental in bridging the gap between theoretical AI research and practical, high-impact business applications. You will design, develop, and deploy a range of machine learning models, from sophisticated recommendation systems and predictive analytics tools to fine-tuned generative AI solutions for enterprise challenges. Working with diverse datasets including text, images, and structured data, you will build robust, end-to-end AI pipelines. You will collaborate closely with product managers and data scientists to define problem spaces and deliver scalable, efficient, and cost-effective AI systems. This position requires a hands-on engineer passionate about leveraging the latest advancements in AI to solve real-world problems and drive measurable outcomes.
Requirements
1. 3-5 years of professional experience in an AI, machine learning, or data science role with a focus on deployment.
2. Strong proficiency in Python and associated ML libraries (e.g., scikit-learn, Pandas, NumPy).
3. Hands-on experience with at least one major deep learning framework, such as TensorFlow or PyTorch.
4. Demonstrable experience deploying and managing ML models on a major cloud platform (AWS SageMaker, Google AI Platform, Azure ML).
5. Proven experience with LLM fine-tuning techniques (e.g., LoRA, full fine-tuning) and the Transformer architecture.
6. Practical knowledge of building systems with vector databases (e.g., Pinecone, Milvus, Weaviate) and Retrieval-Augmented Generation (RAG).
7. Experience designing and implementing end-to-end MLOps pipelines for model training, validation, and serving.
8. Solid understanding of software engineering best practices, including version control, testing, and CI/CD.
Desirable
1. Experience with containerization (Docker) and orchestration (Kubernetes) for deploying scalable services.
2. Familiarity with data processing at scale using tools like Apache Spark or Dask.
3. Contributions to open-source AI/ML projects or a portfolio of relevant personal projects.
4. Experience with model optimization techniques such as quantization, pruning, or knowledge distillation.
5. Strong communication skills with experience presenting complex technical concepts to non-technical stakeholders.
Role Highlights
π° Compensation
AED 45,000 β AED 55,000
πΌ Work Location Type
Hybrid
β Experience
3β5 years of experience in machine learning, data science, or AI engineering.
π’ Department
Information Technology
π Industry
Technology, Information & Media
πΉ Sub-Industry
AI Development