Senior AI Engineer

ExamsTutor

Engineering & Technology

Role Overview

We are looking for a highly skilled and passionate AI/ML Engineer to take on the critical task of building the "brains" of our platform: our personalized, multilingual AI Tutor. You will be responsible for the entire lifecycle of our proprietary Large Language Models (LLMs), from data processing and fine-tuning to API deployment. This is a unique opportunity to work with cutting-edge models like Llama 4 and Mistral 7B and see your work directly impact the lives of millions of students.

Key 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).

Required Skills & 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.

Why Join ExamsTutorAI?

• High Impact: Your work will be at the absolute core of our product and will directly shape the future of education for millions.

• Cutting-Edge Tech: Get hands-on with the latest in generative AI, working with models like Llama 4 and building a sophisticated AI-first product.

• Growth Opportunity: As an early member of the technical team, you'll have a significant influence on our technical direction and culture.

• Strong Team: Work alongside a dedicated and ambitious team backed by global accelerators and partners.

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 protected] with the subject line "AI/ML Engineer Application" before the deadline on Sunday, August 24, 2025.

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