Overview
We are seeking a highly motivated AI Engineer Intern to join our core AI team at Vaiu AI. This role is ideal for candidates who have hands-on experience with deep learning research, model training / fine-tuning, and open-source contributions not just API-based GenAI workflows. You will work on building and improving real AI systems behind our voice agents and intelligent automation platform. Based on performance, successful interns will be converted to full-time AI Engineers after 6 months.
Position Details
- Role Type: Internship (with potential for full-time conversion)
- Duration: 2 months probationary period
- Stipend: As per industry standards
Conversion: Performance-based confirmation to full-time role after 6 months
Key Responsibilities
- Design, train, fine-tune, and evaluate deep learning models for speech, NLP, and conversational AI tasks
- Conduct experiments, ablation studies, and performance benchmarking on models and datasets
- Implement and reproduce research papers in areas such as ASR, TTS, LLMs, multimodal models, or speech understanding
- Build and maintain data pipelines for training and evaluation
- Optimize models for inference efficiency and production deployment
- Collaborate with product and engineering teams to integrate research outputs into real systems
- Document experiments, results, and research findings clearly
Required Skills & Qualifications
Must Have:
- Strong foundation in Deep Learning and Machine Learning fundamentals
- Hands-on experience with PyTorch or TensorFlow (PyTorch preferred)
- Experience training / fine-tuning models (not only calling APIs)
- Experience working on research-style projects, experiments, or thesis work
- Familiarity with reading and implementing research papers
- Strong Python programming skills
- Experience with Git and collaborative development
- Solid understanding of model evaluation, metrics, and debugging
Highly Preferred / Differentiators:
- Published or submitted research papers in deep learning / ML conferences or journals
- Open-source contributions related to ML / DL frameworks, models, or tooling
- Experience in NLP, Speech (ASR / TTS), LLMs, or Conversational AI
- Experience fine-tuning LLMs, diffusion models, or speech models
- Knowledge of training pipelines, distributed training, or experiment tracking (W&B, MLflow, etc.)
- Experience deploying models or optimizing inference (ONNX, TorchScript, quantization, etc.)
What You’ll Work On
- Core model training and fine-tuning for voice agents and conversational AI
- Research-driven improvements to speech recognition, intent understanding, and dialogue systems
- Building experimental prototypes and translating research into production features
- Contributing to internal ML tooling and open-source components
Growth Path
This internship is designed as a direct pathway to a full-time AI Engineer / Research Engineer role. High-performing interns will be offered a permanent position with competitive compensation and the opportunity to work on cutting-edge applied AI research.
How to Apply
Please share:
- Updated resume / CV
- GitHub profile (mandatory)
- Links to research papers, preprints, or technical blogs (if any)
- Brief description of ML / DL projects and experiments you’ve worked on
- Any open-source contributions or model demos
Please apply here!