Chief Language Model Architect

2 weeks ago

India beBeeArtificialintelligence Full time ₹ 15,00,000 - ₹ 28,00,000
Lead AI Engineer

We are seeking an experienced and skilled Lead AI Engineer to join our team. The successful candidate will own the narrative engine, content generation, safety/moderation systems, and personalization logic for a next-generation consumer AI product.

The role focuses on building lightweight, optimized language models that generate safe, structured, and engaging interactions, deployable on both edge devices and the cloud.

Responsibilities:
  • Design and implement lightweight LLM pipelines (Phi-2, TinyLLaMA, Mistral-small, etc.) for structured, interactive outputs.
  • Build branching narrative/interaction flows with deterministic continuation and constrained decoding.
  • Develop moderation and safety layers: rule-based filters, toxicity detection (Detoxify), and fallback to external moderation APIs (e.g., GPT/Claude).
  • Apply content filtering and vocabulary controls to enforce safe, compliant outputs.
  • Implement heuristics-based personalization and progress tracking for adaptive experiences.
  • Optimize models for offline-first inference (quantization, ONNX, GGUF/ggml) with cloud fallback when needed.
  • Build internal tools for prompt/template management, content testing, and moderation review.
  • Work closely with the Speech AI Engineer to integrate text generation voice pipeline seamlessly.
  • Define observability metrics (latency, generation success, moderation outcomes).
Qualifications:
  • 5+ years of professional experience in applied AI/NLP, with at least 3 years focused on LLMs or conversational AI.
  • Strong background in language models: fine-tuning, LoRA, adapter methods, prompt engineering.
  • Proficiency in PyTorch; experience serving models with FastAPI/Docker.
  • Experience with edge optimization: quantization, batching, caching.
  • Knowledge of structured AI outputs (JSON schemas, branching graphs).
  • Hands-on with content moderation systems and multi-layer safety approaches.
  • Understanding of privacy and compliance requirements for consumer AI apps.
Benefits:
  • Opportunity to work on cutting-edge AI projects.
  • Collaborative and dynamic work environment.
  • Professional growth and development opportunities.

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