About the Role

We are looking for ambitious engineering students for our Fes office to tackle complex challenges in Artificial Intelligence and Data Engineering. You will work on building next-generation systems that handle massive scale and real-time decision-making.

Candidates may apply for one of the following two tracks.

Project A: Real-Time Large Scale Knowledge Graph

• The Mission: Design and implement a dynamic Knowledge Graph system capable of ingesting data from "firehose" APIs, scraping huge online databases, and processing real-time streams to map complex relationships instantly.
• Key Responsibilities:
• Pipeline Architecture: Build scalable ETL pipelines to consume data from diverse sources (REST APIs, unstructured web data, SQL dumps).
• Graph Modeling: Design ontologies to represent complex entities and relationships.
• Real-Time Ingestion: Implement streaming architecture to update the graph in near real-time without downtime.
• Query Optimization: Optimize graph traversal queries for low-latency retrieval.
• Tech Stack:
• Graph DBs: Neo4j
• Big Data/Streaming: Apache Kafka, Apache Spark, Flink
• Languages: Python, Java, or Scala

Project B: Constraint-Based AutoML Engine

• The Mission: Develop an Automated Machine Learning (AutoML) engine that goes beyond standard hyperparameter tuning. This engine must build models that strictly adhere to specific business, physical, or hardware constraints (e.g., maximum inference time, memory footprint limits, interpretability rules).
• Key Responsibilities:
• Search Space Optimization: Create algorithms to efficiently search for model architectures that fit defined constraints.
• Constraint Satisfaction: Integrate Operations Research (OR) techniques with ML pipelines to reject non-compliant models early.
• Meta-Learning: Implement systems that "learn how to learn" from previous tasks to speed up convergence.
• Benchmarking: Build a robust evaluation suite to test model performance against constraints.
• Tech Stack:
• ML Frameworks: PyTorch, TensorFlow, Scikit-learn
• Optimization: Google OR-Tools, CP-SAT, Optuna
• AutoML: Custom implementations or extensions of AutoKeras/H2O

Required Profile & Skills

• Minimum Qualifications:
• Final year engineering student (Bac+5) in Computer Science, AI, or Data Science
• Strong proficiency in Python
• Solid understanding of Data Structures and Algorithms
• Familiarity with Git version control
• Good command of English (technical reading/writing)
• Preferred Skills (Bonus):
• For Project A: Experience with NoSQL databases, web scraping (Scrapy/Selenium), and Docker/Kubernetes
• For Project B: Knowledge of Mathematical Optimization (Linear Programming), Bayesian Optimization, or Genetic Algorithms

What We Offer

• Mentorship: Weekly code reviews and guidance from senior architects
• Impact: Your code will not be a "toy project"; it is intended for production use
• Future: Opportunity for a full-time contract (CDI) in Fes upon successful completion

How to Apply

Please apply or send your CV to join@agroconform.com and a brief cover letter mentioning which Project (A or B) you are interested in.