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AI/ML Engineer

ExamsTutor
Nigeria
1 day ago
Today
E

AI/ML Engineer

ExamsTutor

Engineering & Technology

Rest of Nigeria (Nationwide)
Confidential
  • Minimum Qualification :

Job Description/Requirements


Responsibilities

Data Engineering & Preparation: Ingest, parse (from PDFs and other formats), and structure our unique dataset of JAMB/WAEC curriculum, past questions, and textbooks into a pristine, model-ready format (JSONL).

Model Fine-Tuning: Implement and manage the fine-tuning process for open-source LLMs (e.g., Mistral 7B, Llama 4 Maverick) using Parameter-Efficient Fine-Tuning (PEFT/LoRA) techniques on a cloud GPU environment.

Quantization & Optimization: Quantize and optimize fine-tuned models (e.g., to 4-bit) for efficient on-device, offline inference in our mobile application.

API Development: Develop, test, and deploy a scalable, high-performance API (using FastAPI) that exposes the AI Tutor's core capabilities.

Prompt Engineering: Design, test, and refine sophisticated prompts and "meta-prompts" to enable the AI to perform complex tasks, such as generating step-by-step reasoning, personalized study plans, and comprehensive classroom analytics reports.

RAG Implementation: Implement a Retrieval-Augmented Generation (RAG) system using vector databases to provide the AI with deep knowledge from our textbook library.

Deployment & MLOps: Containerize the AI/ML services using Docker and manage their deployment and maintenance on our cloud infrastructure (AWS).


Qualifications

Strong proficiency in Python and common ML/Data Science libraries (PyTorch, Pandas, etc.).

  • Hands-on experience with the Hugging Face ecosystem (transformers, datasets, peft).
  • Demonstrable experience in fine-tuning and deploying Large Language Models (LLMs).
  • Solid understanding of PEFT techniques like LoRA and quantization methods.
  • Experience building and deploying RESTful APIs (FastAPI or Flask is a strong plus).
  • Familiarity with containerization (Docker) and cloud platforms (AWS, GCP, or Azure).
  • A proactive, problem-solving mindset and the ability to work independently.


How to Apply:

Please submit your CV and a brief cover letter or a link to your portfolio/GitHub profile showcasing your relevant projects to [Email Address to be Inserted] with the subject line "AI/ML Engineer Application" before the deadline on Friday, August 22, 2025.


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