Ai/ml engineer
5 days ago
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 Tensor Flow or Py Torch.
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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