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Applied AI Engineer

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

  • 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

  • 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 Highlights
💰 Compensation
AED 45,000 – AED 55,000
📍 Location
Dubai, UAE
💼 Work Location Type
Hybrid
📄 Employment Type
Full-time
📈 Job Level
Mid Level
⌛ Experience
3–5 years of experience in machine learning, data science, or AI engineering.
🏢 Department
Information Technology
🏭 Industry
Technology, Information & Media
🔹 Sub-Industry
AI Development
Getting StartedA few quick details so we know how to reach you
How did you hear about us? *
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Email *(Please ensure the email matches the one mentioned in your CV or resume)
LinkedIn Profile URL *
Please provide your current and expected salary in the box below (with currency): *
Please mention your notice period *
Let’s Get to Know You BetterA few short questions to understand your experience and what you enjoy doing
1. Do you have at least 3 years of professional experience deploying machine learning models into production environments? *
2. Have you fine-tuned a large language model and integrated it into an application using a RAG architecture? *
3. Do you have hands-on experience using a managed AI platform like AWS SageMaker, Google AI Platform, or Azure Machine Learning for model deployment? *
4. Have you built an automated, end-to-end machine learning pipeline from data ingestion to model inference? *
5. Does your experience include building models using both structured (e.g., tabular) and unstructured (e.g., text, image) data? *
6. Have you been directly responsible for optimizing a production machine learning model for cost, latency, or throughput? *
Final DetailsSalary expectations and any supporting credentials
1. Where does your salary sit today (so we can help it move up tomorrow)?*
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2. What’s the number that’ll make you say "this is worth it"?*
Per month, in the currency mentioned
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Frequently Asked Questions (FAQs)Have a question? Check here for quick answers

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.