Applied AI Engineer
Information Technology
Dubai, UAE
Hybrid
Full-time
Mid Level
3–5 years of experience in machine learning, data science, or AI engineering.
Posted May 8, 2025
About the role
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
- 3-5 years of professional experience in an AI, machine learning, or data science role with a focus on deployment.
- Strong proficiency in Python and associated ML libraries (e.g., scikit-learn, Pandas, NumPy).
- Hands-on experience with at least one major deep learning framework, such as TensorFlow or PyTorch.
- Demonstrable experience deploying and managing ML models on a major cloud platform (AWS SageMaker, Google AI Platform, Azure ML).
- Proven experience with LLM fine-tuning techniques (e.g., LoRA, full fine-tuning) and the Transformer architecture.
- Practical knowledge of building systems with vector databases (e.g., Pinecone, Milvus, Weaviate) and Retrieval-Augmented Generation (RAG).
- Experience designing and implementing end-to-end MLOps pipelines for model training, validation, and serving.
- Solid understanding of software engineering best practices, including version control, testing, and CI/CD.
Desirable skills
- Experience with containerization (Docker) and orchestration (Kubernetes) for deploying scalable services.
- Familiarity with data processing at scale using tools like Apache Spark or Dask.
- Contributions to open-source AI/ML projects or a portfolio of relevant personal projects.
- Experience with model optimization techniques such as quantization, pruning, or knowledge distillation.
- Strong communication skills with experience presenting complex technical concepts to non-technical stakeholders.
Role details
- Department
- Information Technology
- Location
- Dubai, UAE
- Work setup
- Hybrid
- Employment type
- Full-time
- Job level
- Mid Level
- Experience
- 3–5 years of experience in machine learning, data science, or AI engineering.
- Industry
- Technology, Information & Media
- Sub-industry
- AI Development
- Compensation
- AED 45,000 – AED 55,000
Frequently asked questions
This recruitment process is being managed by byteSpark.ai. Further information about the employing organisation, team, and business context will be shared with shortlisted candidates at the appropriate stage.
This role is for an engineer who wants to build AI systems that leave the notebook and create measurable business impact. You will turn emerging AI capabilities into scalable applications spanning recommendation systems, predictive analytics, multimodal processing, and enterprise Generative AI.
The successful candidate will design, fine-tune, deploy, and improve production AI solutions using structured and unstructured data, including text, images, audio, and video. The work may involve LLM fine-tuning, Retrieval-Augmented Generation, vector databases, real-time model serving, and complete machine learning pipelines.
The strongest candidates will have approximately 3 to 5 years of hands-on AI, machine learning, or data science experience with clear evidence of production deployment. They should be proficient in Python, TensorFlow or PyTorch, cloud AI platforms, MLOps, software engineering, testing, and CI/CD rather than having only research or proof-of-concept experience.
No. Model quality is only part of the challenge. The Applied AI Engineer will also be responsible for reliability, scalability, latency, monitoring, and cost efficiency. Candidates who have optimised production models through quantisation, pruning, orchestration, infrastructure choices, or improved retrieval strategies will be particularly relevant.