Lead AI Engineer (LLMs & Interactive AI)

5 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

About the Role

AI Engineer specializing in LLMs & Interactive AI

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.

Nice to Have

  • Experience with

    dialogue systems

    or conversational assistants.
  • Exposure to

    personalization/recommendation systems

    .
  • Familiarity with

    educational/narrative applications

    (general, not product-specific).
  • Graduated from IITs/NITs/Tier 1 Colleges


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