AI / ML Engineer

Ekrocx Technologies is a digital transformation consultancy helping enterprise brands build and scale next-generation commerce, data, and analytics solutions across the GCC and beyond. We partner with leading retailers, CPG companies, and B2B organisations to unlock measurable growth through technology and insight.

By combining deep technical expertise with strategic business understanding, we deliver reliable, scalable solutions that enable our clients to innovate faster, streamline operations, and stay ahead in an ever-evolving digital landscape.

About the Role

Join Ekrocx's AI practice and build intelligent systems that make enterprise commerce smarter — from product recommendation engines to LLM-powered search, dynamic pricing models, and demand forecasting. You'll work on production AI systems deployed at scale, with real business impact from day one.

Responsibilities

• Design, train, and deploy machine learning models for recommendation, search ranking, and demand forecasting.
• Build LLM-powered features including semantic search, product Q&A, and merchandising automation.
• Develop ML pipelines for feature engineering, model training, evaluation, and serving.
• Collaborate with Data Architects to ensure clean, reliable feature stores and training data.
• Implement A/B testing frameworks to measure model performance against business KPIs.
• Monitor deployed models for drift, degradation, and performance regressions.
• Research and evaluate emerging AI techniques relevant to commerce and retail use cases.

Requirements

• 4+ years of experience building and deploying ML models in production environments.
• Strong Python skills — NumPy, Pandas, scikit-learn, PyTorch or TensorFlow.
• Experience with LLMs: fine-tuning, RAG pipelines, prompt engineering, and evaluation frameworks.
• Familiarity with MLOps tooling: MLflow, Weights & Biases, or similar.
• Solid understanding of recommendation system architectures (collaborative filtering, content-based, hybrid).
• Experience working with large-scale datasets on cloud platforms.

Nice to Have

• Experience with vector databases (Pinecone, Weaviate, or pgvector).
• Knowledge of personalisation platforms (Dynamic Yield, Bloomreach).
• Exposure to retail / CPG-specific ML challenges: demand sensing, markdown optimisation.
• Published research papers or conference presentations.

Benefits

• Competitive salary and performance-based bonuses.
• Flexible working arrangements — remote-friendly with global office access.
• AED 8,000 annual learning and development budget.
• Full health, dental, and vision coverage from day one.
• Access to a senior mentorship network across all disciplines.
• Regular team off-sites, knowledge-sharing sessions, and career reviews.