Description
Role Objective
As a Junior AI Engineer, you will be the technical engine behind Tribal AI, IP-Tribe’s flagship LLMOps platform. You will develop, tune, and integrate Large Language Models (LLMs) to create high-impact demos, MVPs, and solutions for Tier-1telecommunications and business enterprises.
Key Responsibilities
AI Use-Case Integration: Design and implement end-to-end AI workflows by integrating LLMs into functional business applications (e.g., automated customer support, network log analysis, or intelligent outage prediction).
Model Fine-Tuning & Optimisation: Perform supervised fine-tuning (SFT) and parameter tuning (hyperparameters, LoRA/QLoRA) within the Tribal AI environment to adapt base models to domain-specific telco data. (Good to have but not compulsory)
Rapid MVP Development: Use Python to build custom operators, data connectors, and API wrappers that extend the Tribal AI platform’s core capabilities.
ML Modelling: Apply classical machine learning and statistical modelling techniques when LLMs alone aren't sufficient, ensuring the "right tool for the right job."
RAG Architecture: Build and optimise Retrieval-Augmented Generation(RAG) pipelines, focusing on chunking strategies, embedding selection, and vector database management.
Performance Benchmarking: Evaluate model outputs using testing tools to ensure accuracy, reduced hallucination, and compliance with enterprise security standards.
Technical Skill Requirements
Core Programming: Advanced Python coding skills (Pandas, NumPy, Scikit-learn, FastAPI/Flask).
ML Fundamentals: A solid working knowledge of machine learning theory, including supervised/unsupervised learning, model evaluation metrics, and feature engineering.
LLM Proficiency: * Experience integrating LLMs (OpenAI, Gemini, Llama, Qwen, or DeepSeek) into software applications.
Understanding of Model Parameters (Temperature, Top-P, Context Windows) and their impact on output.
Practical project experience in Prompt Engineering and Chain-of-Thought reasoning.
Infrastructure: Comfortable working in Linux environments and using Docker for containerised deployments.
Preferred Qualifications
Project Portfolio: Demonstrated experience through a GitHub repository or portfolio showcasing completed ML/AI projects (e.g., chatbots, sentiment analysers, or predictive models).
Tooling: Familiarity with Tools that enable AI/Agentic workflow, MLflow or Vector DBs
Education: Degree in Computer Science, Data Science, or a related field with a strong emphasis on AI/ML.
Educational Qualifications
Bachelor’s Degree in applied artificial intelligence, Computer Science, or similar capacity
Completed projects using AI techstack
Good understanding of Object-Oriented Programming
Full-stack development and a good understanding of SDLC
Experienced working in a project team
Why Join IP-Tribe?
You will work at the intersection of 5G infrastructure and Enterprise AI. This role offers the unique opportunity to master the industry-leading LLMOps platform, while building the future of"Tribal AI" for major telecommunications players and enterprise markets.