AI Research Intern

Position Overview

We are seeking a motivated Research Intern to join our AI research team, focusing on Text-to-Speech (TTS) and Automatic Speech Recognition (ASR) technologies. The intern will play a crucial role in evaluating our proprietary models against industry benchmarks, analyzing competitive voice agent platforms, and contributing to cutting-edge research in speech AI technologies.

Skills & Competencies

Technical Competencies

• Strong analytical and problem-solving abilities
• Ability to design and conduct rigorous experiments
• Experience with statistical analysis and performance metrics
• Understanding of audio signal processing fundamentals
• Knowledge of distributed training and large-scale model development

Soft Skills

• Excellent written and verbal communication skills
• Ability to work independently and manage multiple projects
• Strong attention to detail and commitment to reproducible research
• Collaborative mindset and ability to work in cross-functional teams
• Curiosity and passion for staying current with AI research trends

Duration and Compensation

Duration: 6 months

Compensation: Monthly Stipend: Base stipend of INR 8,000 per month, with the potential to increase up to INR 15,000 based on performance evaluations.

Performance-Based Pay Scale: Eligibility for monthly performance-based bonuses, rewarding exceptional project contributions and teamwork.

Additional Benefits: Access to professional development opportunities, including workshops, tech talks, and mentoring sessions.

What You'll Gain

Learning Opportunities

• Hands-on experience with state-of-the-art speech AI technologies
• Exposure to full model development lifecycle from research to deployment
• Mentorship from experienced AI researchers and engineers
• Opportunity to contribute to cutting-edge research projects

Professional Development

• Experience with industry-standard tools and methodologies
• Opportunity to present research findings to technical and business stakeholders
• Potential for research publication and conference presentations
• Networking opportunities within the AI research community

Key Responsibilities

• Conduct comprehensive evaluation of our TTS and ASR models against existing state-of-the-art models
• Design and implement evaluation metrics and frameworks for speech quality assessment
• Perform comparative analysis of model performance across different datasets and use cases
• Generate detailed reports on model strengths, weaknesses, and improvement opportunities
• Evaluate and compare our voice agent platform with existing solutions (Vapi, Bland AI, and other competitors)
• Analyze feature sets, performance metrics, and user experience across different voice agent platforms
• Conduct technical deep-dives into competitive architectures and methodologies
• Provide strategic recommendations based on competitive landscape analysis
• Monitor and analyze emerging trends in ASR, TTS, and voice AI technologies
• Research novel approaches to improve ASR and TTS model performance
• Investigate new architectures, training techniques, and optimization methods
• Stay current with academic literature and industry developments in speech AI
• Assist in training TTS and ASR models on various datasets
• Implement and experiment with different model architectures and configurations
• Perform model fine-tuning for specific use cases and domains
• Optimize models for different deployment scenarios (edge, cloud, real-time)
• Conduct data preprocessing and augmentation for training datasets
• Maintain detailed documentation of experiments, methodologies, and results
• Create visualization and analysis tools for model performance tracking
• Prepare technical reports and presentations for internal stakeholders

Requirements

• Programming Languages: Proficiency in Python; experience with PyTorch, TensorFlow
• Speech AI Frameworks: Experience with libraries like librosa, torchaudio, speechbrain, or similar
• Machine Learning: Strong understanding of deep learning architectures, training procedures, and evaluation methods
• Data Processing: Experience with audio data preprocessing, feature extraction, and dataset management
• Tools & Platforms: Familiarity with Colab or Jupyter notebooks, Git, Docker, and cloud platforms (AWS/GCP/Azure)
• Knowledge of speech synthesis techniques (WaveNet, Tacotron, FastSpeech, etc.)
• Understanding of ASR architectures (Wav2Vec, Whisper, Conformer, etc.)
• Experience with model optimization techniques (quantization, pruning, distillation)
• Familiarity with MLOps tools and model deployment pipelines
• Previous work with voice AI applications or conversational AI systems preferred