- Company Name
- Triveni IT
- Job Title
- Artificial Intelligence Engineer
- Job Description
-
Job title: Artificial Intelligence Engineer
Role Summary: Design, implement, and optimize browser‑based voice recognition interfaces, customizing Web Speech API and related frameworks across major browsers and devices to deliver accurate, responsive, and accessible voice interactions for consumers and enterprise users.
Expactations: Deliver production‑ready voice solutions that meet strict performance, accuracy, and noise‑resilience criteria; ensure cross‑browser, cross‑device consistency; collaborate tightly with product, design, and engineering teams; maintain inclusive and accessible voice experiences; iterate on models and features for multilingual support and configurable speech durations.
Key Responsibilities: • Architect and build speech interfaces using Web Speech API on Chrome, Edge, Safari, Firefox, and other browsers.
• Extend and customize API functionality to improve speed, accuracy, and noise resilience.
• Benchmark performance, fine‑tune models, and implement noise‑suppression techniques.
• Ensure cross‑device compatibility (desktop, laptop, tablet, smartphone) and responsive UI/UX.
• Integrate voice features with product workflows, design prototypes, and API layers.
• Support multilingual voice recognition and configurable audio capture parameters.
• Collaborate with accessibility experts to build inclusive interfaces.
• Evaluate and prototype alternative speech engines (Kaldi, DeepSpeech, etc.) for potential deployment.
Required Skills: • Proven experience delivering voice recognition solutions across multiple browsers.
• Deep knowledge of Web Speech API and ability to extend/customize it.
• Strong performance optimization and benchmarking skills for speech models.
• Expertise in noise robustness, speed, and accuracy enhancements.
• Multilingual voice support and configurable duration handling.
• Familiarity with alternative speech frameworks (Kaldi, DeepSpeech, etc.).
• Experience building accessible, inclusive voice interfaces.
• Collaborative mindset for product, design, and engineering teamwork.
• Background in NLP or machine‑learning techniques relevant to speech.
Required Education & Certifications: • Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Speech‑Language Technology, or a related field.
• Certifications or formal training in speech recognition, artificial intelligence, natural language processing, or machine learning.