
Senior AI Engineer
ProgressSoft · Morocco · Remote
- IT Services & Consulting
- 501–1,000 employees
- Amman
Weak hiring record · median 292 days open
All reasons
- Open 195 days
- 82% of this employer's openings are over 60 days old
In its favour
- Still listed on the employer's own board
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.
Skills
- LLM
- Azure AI Services
- Machine Learning
- Deep Learning
- Hugging Face Transformers
- Generative AI
- Retrieval-Augmented Generation
- Airflow
- Prefect
- Python
- PyTorch
- TensorFlow
- scikit-learn
- Pandas
- NumPy
- Matplotlib
- Plotly
- LangChain
- MLflow
- Git
- C++
- C#
- Docker
- Kubernetes
- Vector Databases
- Power BI
- Tableau
- Streamlit
- MLOps
- LLMOps
- DVC
- Weights & Biases
- Spark
- PySpark
- Databricks
- EMR
- GCP
- Dataproc
- SQL
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