Senior AI Engineer

We are looking to hire passionate Senior AI Engineers to help turn data into intelligent, production-ready solutions. You will work across the full AI stack: traditional machine-learning models, large language models (LLMs), computer-vision pipelines, and analytics / forecasting workflows. If you enjoy exploring data, building state-of-the-art models, and shipping reliable AI services, we would love to meet you.
Responsibilities

- Model Development – Design, train, fine-tune, and evaluate models spanning classical ML, deep learning (CNNs, transformers), and generative AI (LLMs, diffusion).

- Data Exploration & Analytics – Conduct exploratory data analysis, statistical testing, and time-series / forecasting to inform features, prompts, and business KPIs.

- End-to-End Pipelines – Build reproducible workflows for data ingestion, feature engineering / prompt stores, training, CI/CD, and automated monitoring.

- LLM & Agentic AI Engineering – Craft prompts, retrieval-augmented generation (RAG) pipelines, and autonomous/assistive agents; fine-tune LLMs on domain-specific datasets to boost accuracy and align outputs with product requirements.

- AI Automation & Integration – Expose AI components as micro-services and event-driven workflows; integrate with orchestration tools (Airflow, Prefect) and business APIs to automate decision pipelines.

- Continuous Learning – Track advances in LLMs, vision, and analytics; share insights and best practices with the wider engineering team.

- Mentor junior engineers and contribute to technical direction and engineering best practices.

Requirements

- BSc in Computer Science, Mathematics, or related field.

- 5+ years of professional experience working on AI/ML projects.

- Good command of English and Arabic (written and spoken).

- Proficient in Python and core libraries (PyTorch / TensorFlow, scikit-learn, pandas, NumPy).

- Solid understanding of machine-learning algorithms, deep-learning fundamentals, and basic statistics.

- Experience with data wrangling and visualization (Matplotlib / Plotly) and exploratory analysis.

- Familiarity with at least one of: OpenCV, Hugging Face Transformers, LangChain, MLflow, or similar.

- Good grasp of software-engineering best practices: Git, code reviews, testing, CI.

Preferred Qualifications

- Knowledge of C++ or C# for performance-critical modules.

- Experience deploying models via Docker, Kubernetes, or cloud AI services.

- Exposure to vector databases and RAG workflows.

- Skill in BI / dashboard tools (Power BI, Tableau, Streamlit) or time-series frameworks (Prophet, statsmodels).

- Familiarity with MLOps / LLMOps tooling (DVC, MLflow Tracking, Weights & Biases, BentoML).

- Experience with image processing techniques (e.g., OpenCV, image segmentation, feature extraction)

- Experience with Spark (PySpark) and distributed data processing, including usage of platforms such as Databricks, AWS EMR, or GCP Dataproc.

- Strong SQL skills and experience working with large-scale datasets, including partitioning and performance tuning.

- Familiarity with modern data lake architectures and scalable data storage concepts.

Originally posted on Himalayas