AI/ML Engineer

3 days ago


Chennai, Tamil Nadu, India Zudu Full time

Job Description: We are seeking a skilled AI/ML Engineer specializing in Conversational AI to join our dynamic team. The ideal candidate will possess expertise in developing and optimizing AI-driven voice agents, focusing on large language models (LLMs), prompt engineering, and voice-specific integrations. You will play a pivotal role in enhancing our AI voice automation platform, ensuring seamless and natural interactions for end-users.​ Key Responsibilities: Model Development and Optimization: Fine-tune and adapt foundation LLMs for conversational interfaces.​ Implement model quantization and optimization techniques to meet deployment constraints.​ Manage token usage and context window strategies to optimize performance.​ Develop and integrate retrieval-augmented generation (RAG) systems for enhanced response accuracy.​ Prompt Engineering: Design robust system prompts that maintain agent persona and capabilities.​ Handle multi-turn conversations with effective context retention.​ Control output format, length, and style consistently.​ Utilize few-shot learning approaches and exemplar design to improve model responses.​ Evaluation and Testing: Develop automated evaluation frameworks to measure response quality.​ Set up A/B testing infrastructure for prompt and model variants.​ Design metrics to track hallucinations, coherence, and helpfulness.​ Conduct red-teaming exercises to identify edge cases and failure modes.​ Voice-Specific Integration: Integrate Automatic Speech Recognition (ASR) outputs with LLM inputs, implementing robust error handling.​ Synthesize natural-sounding Text-to-Speech (TTS) from LLM responses.​ Manage turn-taking and interruptions in voice conversations effectively.​ Handle speech disfluencies and recognition errors to maintain conversational flow.​ Deployment and Architecture: Develop strategies to minimize latency in real-time voice applications.​ Implement streaming architectures for incremental processing.​ Utilize caching and prediction mechanisms to improve response times.​ Orchestrate multiple models to handle different aspects of the conversation seamlessly.​ Monitoring and Operations: Establish systems to detect and respond to model performance degradation.​ Implement logging frameworks to capture and analyze problematic interactions.​ Develop continuous improvement processes for model and prompt updates.​ Collect feedback through privacy-preserving mechanisms to inform enhancements.​ Qualifications: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.​ Proven experience in fine-tuning and deploying LLMs for conversational AI applications.​ Strong proficiency in Python and familiarity with AI/ML frameworks such as TensorFlow or PyTorch.​ Experience with prompt engineering and designing effective prompts for AI models.​ Knowledge of ASR and TTS technologies and their integration with AI models.​ Understanding of real-time processing and deployment architectures for voice applications.​ Excellent problem-solving skills and the ability to work collaboratively in a team environment.​ By bringing your expertise to our team, you will contribute to the advancement of our AI voice automation platform, delivering human-like interactions and driving innovation in voice AI technology.​


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