AIML Engineer

1 day ago

Bengaluru, Karnataka, India Movius Full time ₹ 15,00,000 - ₹ 20,00,000 per year

Job Title: AI Engineer / Data Scientist – NLP & LLM Focus

Location:
Bangalore

Role Overview:

We are looking for a hands-on
AI Engineer / Data Scientist
with deep expertise in
Natural Language Processing (NLP)
and
Large Language Models (LLMs)
. The ideal candidate will have experience building custom AI models from the ground up, optimizing for performance, and integrating them into real-world systems and applications.

Key Responsibilities:

  • Design, build, and deploy
    NLP and LLM-based models
    tailored to domain-specific needs (e.g., chatbots, summarization, classification).
  • Fine-tune and adapt
    foundation models
    (e.g., GPT, LLaMA, Mistral) for business use cases.
  • Build
    custom pipelines
    for text processing, entity recognition, language understanding, and speech-to-text integrations.
  • Work closely with engineering teams to
    integrate AI models
    into production systems (APIs, microservices, and edge deployments).
  • Conduct
    experimentation, model evaluations
    , and performance tuning for latency, accuracy, and scalability.
  • Collaborate cross-functionally with product, infra, and DevOps teams to ensure smooth
    deployment and monitoring
    of models.

Required Skills & Experience:

  • Strong experience with
    Python
    ,
    PyTorch
    , or
    TensorFlow
    .
  • Proven track record in
    training, fine-tuning
    , and
    deploying LLMs
    or transformer-based models (BERT, GPT, T5, etc.).
  • Solid understanding of
    NLP fundamentals
    – tokenization, embeddings, attention, text classification, sequence labeling, etc.
  • Experience with
    model deployment tools
    : FastAPI, Flask, Docker, REST APIs.
  • Exposure to
    data pipelines
    and
    MLOps tools
    (MLflow, Weights & Biases, SageMaker, etc.).
  • Knowledge of
    speech-based interfaces
    or integration with
    telephony/speech systems
    is a strong plus.
  • Ability to translate business problems into AI solutions.
  • Experience with
    RAG (Retrieval Augmented Generation)
    pipelines.
  • Familiarity with
    LangChain, LlamaIndex
    , or similar agentic/LLM orchestration tools.
  • Understanding of
    model security, prompt injection risks
    , and
    observability
    .

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