Machine Learning (ML)
PythonResearch 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.
Key Responsibilities
Model Evaluation & Benchmarking
- 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
Competitive Analysis
- 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
Research & Innovation
- 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
Model Development & Training
- 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
Documentation & Reporting
- Maintain detailed documentation of experiments, methodologies, and results
- Prepare technical reports and presentations for internal stakeholders
- Contribute to research publications and technical blog posts
- Create visualization and analysis tools for model performance tracking
Required Qualifications
Education & Experience
- Currently pursuing or recently completed Bachelor's/Master's degree in Computer Science, Electrical Engineering, Machine Learning, or related field
- Strong academic background in machine learning, deep learning, and signal processing
- Previous experience with speech processing, NLP, or audio ML projects (academic or professional)
Technical Skills
- 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)
Preferred Qualifications
- Experience with transformer architectures, attention mechanisms, and sequence-to-sequence models
- 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
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
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
Shubham Vishwakarma
Full Stack Developer - Averlon
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Full Stack Developer - Averlon