About the Role
You will collaborate on building and improving NLP models and machine learning pipelines used in real-time voice interaction platforms. Your work will involve data processing, model experimentation, and integration into production systems.
Responsibilities
- Assist in designing and training NLP models for speech understanding
- Process and annotate datasets used for model training
- Evaluate model performance using defined metrics
- Support the development of machine learning pipelines
- Collaborate with engineers to integrate models into voice applications
- Debug and troubleshoot model behavior in real-world scenarios
- Contribute to improving model accuracy and response quality
- Work with speech recognition and text-to-speech components
- Help maintain and version model artifacts
- Participate in team discussions on model improvements
- Write clean, maintainable code for ML workflows
- Monitor model performance in production environments
- Assist in creating automated testing for NLP components
- Document model configurations and experimental results
- Stay updated with advancements in NLP and ML techniques
- Optimize inference speed and resource usage
- Support data preprocessing and cleaning pipelines
- Contribute to error analysis for model outputs
- Work with APIs that serve machine learning models
- Follow best practices in machine learning engineering
- Use version control for code and model tracking
- Collaborate across technical teams to align on goals
- Ensure data privacy and handling compliance
- Test models across diverse linguistic inputs
- Contribute to improving system robustness
Compensation
Hourly wage based on experience
Work Arrangement
Hybrid
Team
Small, agile team focused on AI-driven voice solutions
What We Offer
- Flexible working hours to accommodate studies
- Opportunity to work on cutting-edge voice AI technology
- Close mentorship from experienced engineers
- Exposure to real-world deployment of machine learning models
- Collaborative and inclusive team culture
Application Process
- Submit your resume and cover letter
- Include links to relevant projects or code repositories
- Shortlisted candidates will be invited for a technical interview
- Final stage includes a practical coding task
- We aim to respond within two weeks of application
Not offered
