Design, build, evaluate, and deploy machine learning models for real-world AI applications.
Work across multiple ML domains such as computer vision, NLP/LLMs, MLOps, and audio AI.
Develop AI solutions that can operate in on-premises, edge, hybrid, and cloud environments.
Translate ambiguous business or operational problems into structured ML approaches.
Evaluate problems from different machine learning perspectives and select the most suitable technical path.
Apply strong mathematical reasoning to model selection, model design, validation, and performance evaluation.
Build scalable ML pipelines, inference workflows, and deployment-ready AI systems.
Work closely with engineering, product, and research teams to turn prototypes into reliable production systems.
Support deployment standards for environments where cloud-native assumptions may not apply.
Ensure models are tested, monitored, optimized, and production-ready for real-world use cases.

Strong multidisciplinary machine learning background across at least two of the following areas:
***Computer Vision ***
*** NLP / Large Language Models ***
*** MLOps ***
*** Audio AI / Speech AI ***
Strong mathematical foundations in areas such as:
***Linear algebra ***
*** Probability and statistics ***
*** Optimization ***
*** Numerical methods ***
*** Model evaluation and validation***
Hands-on experience deploying AI/ML systems in on-premises and edge device environments.
Familiarity with cloud infrastructure, particularly one or more of: AWS, Microsoft Azure, Microsoft technology stack
Practical experience taking ML models from experimentation to deployment.
Ability to work across different company or project contexts, rather than experience limited to one employer or one broad job title.
Strong understanding of model performance, trade-offs, latency, scalability, and infrastructure constraints.
Experience with production-grade ML engineering, not just research notebooks or proof-of-concepts.

Competitive salary benchmarked to market
Direct exposure to cutting-edge enterprise AI projects across UAE and GCC
Flat team structure
work directly with founders and senior engineers
Opportunity to grow into a Senior or Lead Engineer role
Flexible remote/hybrid work arrangements
Fast-paced environment where your work ships to production and reaches real clients

AI & ML Engineer

Key skills