AI/ML Engineer Intern

Description

We are seeking an AI/ML Engineer Intern for a remote internship role. The intern will be responsible for designing, implementing, and optimizing machine learning models to solve complex challenges. Key responsibilities will include data preprocessing, model training, testing, and deployment. Work on deploying and optimizing ML models directly on mobile devices. Focus on performance, latency, and privacy-first AI. ****** THIS IS UNPAID INTERNSHIP *****

Requirements

Strong Python fundamentals Hands-on with TensorFlow / PyTorch, llama.cpp Understanding of model optimization (quantization, pruning) Basic knowledge of LLMs / embeddings

Responsibilities

Convert and deploy models using TensorFlow Lite / ONNX / Core ML Quantize and optimize models for low memory + battery usage Benchmark latency, memory, and inference performance Work on on-device NLP tasks (summarization, embeddings, intent detection) Collaborate with mobile team for real-world deployment constraints You can make models run fast on weak hardware You understand trade-offs (accuracy vs performance)

Nice to Have

Experience with TFLite / Core ML / ONNX / llama.cpp Exposure to edge AI use cases

Benefits

Direct exposure to building real-world AI systems (LLMs, memory, personalization) Opportunity to work on cutting-edge conversational AI and hybrid models Hands-on experience with embeddings, retrieval, and AI workflows High learning environment with real ownership and experimentation Flexible, remote work structure Potential opportunity for a full-time role based on performance

Skills

Hybrid (Phi/Gemma + GPT API)

FAISS / SQLite memory

Hybrid AI Model

Small on-device model (Phi-3 / Gemma 2B)

Cloud fallback (GPT-4o-mini / Claude)

Embeddings + Memory

FAISS / SQLite (local memory)

LLM Orchestration

Lightweight custom logic