Research, prototype, and develop AI/ML models and end-to-end voice agents (STT, TTS, NLU, LLMs). Build and evaluate prototypes, design experiments and benchmarks, analyze failure modes, optimize inference and pipelines for scalability, and collaborate to productionize conversational voice systems.
𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀
𝗦𝗮𝗹𝗮𝗿𝘆 𝗥𝗮𝗻𝗴𝗲: ₹15,00,000 – ₹25,00,000 (i.e., INR 15–25 LPA)
Experience: 1+ yrs
Location: India
Job Type: Full-time
We are looking for a highly motivated and technically strong Research Engineer with 1–4 years of experience to join our AI/ML team and work on next-generation voice agent technologies. The ideal candidate will have a strong foundation in machine learning, deep learning, natural language processing, and speech technologies, along with a passion for researching and building intelligent conversational systems.
You will work at the intersection of AI research and engineering, transforming emerging techniques into reliable, scalable, and production-ready voice experiences. This role involves experimentation, prototyping, model evaluation, optimization, and hands-on development of AI-powered voice agents.
RequirementsKey Responsibilities
- Research, prototype, and develop AI/ML models and systems for conversational and voice-based applications.
- Design and build intelligent voice agents capable of understanding user intent, maintaining conversational context, and generating natural responses.
- Work with speech-to-text (STT), text-to-speech (TTS), natural language understanding (NLU), and large language models (LLMs) to develop end-to-end voice experiences.
- Experiment with different ML architectures, prompting strategies, model configurations, and agentic workflows to improve accuracy, latency, and conversational quality.
- Develop and evaluate prototypes using Python and modern AI/ML frameworks.
- Research emerging developments in Generative AI, conversational AI, speech AI, multimodal models, and agent architectures and identify opportunities for practical implementation.
- Create evaluation frameworks, benchmarks, and experiments to measure model and voice-agent performance.
- Analyze model outputs, identify failure modes, and develop techniques to improve robustness, relevance, and response quality.
- Collaborate with software engineers, product teams, and researchers to transition successful experiments into production systems.
- Optimize AI/ML pipelines for scalability, inference performance, reliability, and real-time voice interaction.
- Document research findings, technical approaches, experiments, and results.
- 1–4 years of hands-on experience in AI/ML, machine learning engineering, research engineering, or a related field.
- Strong programming skills in Python and familiarity with AI/ML development workflows.
- Solid understanding of machine learning and deep learning concepts, including model training, evaluation, optimization, and inference.
- Hands-on exposure to LLMs, Generative AI, NLP, or conversational AI.
- Strong understanding of voice agent architectures and conversational AI pipelines.
- Familiarity with speech-to-text (STT), text-to-speech (TTS), speech processing, and voice interaction systems.
- Experience working with frameworks and libraries such as PyTorch, TensorFlow, Hugging Face, Transformers, or similar technologies.
- Ability to design experiments, analyze results, troubleshoot model behavior, and iterate rapidly.
- Strong problem-solving and analytical skills with an ability to work on ambiguous research problems.
- Experience building or deploying real-time voice agents.
- Knowledge of RAG, vector databases, embeddings, function calling, tool use, and agentic workflows.
- Familiarity with speech models, audio processing, diarization, wake-word detection, or speech enhancement.
- Experience with APIs and cloud platforms such as AWS, GCP, or Azure.
- Knowledge of model serving, inference optimization, quantization, or low-latency AI systems.
- Exposure to open-source LLMs and speech models.
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related technical field.
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