WorkSpeak helps sales and customer-facing teams practice real-world conversations with an AI partner that can simulate diverse roles, scenarios, and difficulty levels. Team members can rehearse discovery calls, objection handling, presentations, client conversations, and challenging discussions in a safe setting. Each practice session generates actionable coaching to improve communication skills and performance.

For managers and enablement teams, WorkSpeak creates a scalable practice layer between formal training and live customer interactions, supporting more effective and confident teams.

Role Description We are looking for an AI Engineer Intern to work closely with the founder on building and experimenting with this evaluation system.

This is a highly hands-on role. You will work with different LLMs and audio/voice models, design prompts and evaluation pipelines, run experiments, analyse failures, and continuously improve the accuracy, consistency, and latency of AI-generated feedback.

Qualifications

- Strong foundation in Computer Science and Software Engineering, with proficiency in Python and familiarity with core concepts such as data structures, algorithms, APIs, and software development practices.
- Hands-on experience working with Large Language Models (LLMs), including familiarity with model APIs, prompt engineering,



structured outputs, and techniques for improving the reliability of AI-generated responses.
- Understanding of Natural Language Processing and conversational AI concepts, with an interest in applying them to real-world communication and voice-based applications.
- Demonstrated ability to design and run experiments, compare AI models and approaches, analyse outputs, identify failure patterns, and iterate systematically toward improved accuracy and performance.
- Familiarity with multimodal or speech AI technologies, including speech-to-text, audio processing, voice models, or LLMs capable of processing audio, is highly beneficial.
- Ability to think critically about AI evaluation, including designing rubrics, benchmarking model performance, validating scoring consistency, and assessing the quality of generated feedback.
- Strong problem-solving skills and an ability to work independently on ambiguous technical problems, while communicating findings and trade-offs clearly.
- Currently pursuing or recently completed a degree in Computer Science, Artificial Intelligence, Engineering, Data Science, or a related field.
- Familiarity with Git, cloud APIs, backend development frameworks, and AI/ML libraries is beneficial.

📌 AI Engineer – Paid Internship (Dehradun)
🏢 Workspeak
📍 Dehradun