Generative AI

Posted on April 24, 2025

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Job Description

  • Generative AI
  • Responsibilities:
  • * Develop, Train, Finetune, and Deploy large language models for text completion and chats in different applications including coding, NLU, NLG, IRQA, machine translation, and dialog,
  • reasoning, and tool systems.
  • * Apply instruction tuning, reinforcement learning from human feedback (RLHF), and parameter efficient fine tuning such as p-tuning, adaptors, LoRA, and so on to improve LLMs
  • for different use cases.
  • * Measure and benchmark model and application performance
  • * Analyze model accuracy and bias and recommend the next course of action &
  • Improvements.
  • * Maintain model evaluation systems.
  • * Drive the gathering, building, and annotation of domain specific datasets to train LLMs for
  • different tasks and applications.
  • * Gather knowhow on datasets for LLM training & evaluation.
  • * Characterize performance and quality metrics across platforms for various AI and system
  • components.
  • * Participate in developing and reviewing code, design documents, use case reviews, and test plan reviews. � Help innovate, identify problems, recommend solutions, and perform triage in a collaborative team environment.
  • Qualifications:
  • * Master�s degree (or equivalent experience) or PhD in Computer Science, Electrical
  • Engineering, Artificial Intelligence, or Applied Math with 8+ years of experience.
  • * Excellent programming skills in Python with strong fundamentals in programming,
  • optimizations and software design
  • * Strong knowledge of ML/DL techniques, algorithms, and tools with exposure to CNN, RNN
  • (LSTM), Transformers (BERT, BART, GPT/T5, Megatron, LLMs)
  • * Hands-on experience on conversational AI Technologies like Natural Language
  • Understanding, Natural Language Generation, Dialog systems(including system integration,
  • state tracking and action prediction), Information retrieval and Question and Answering,
  • Machine Translation etc.
  • * Experience with Training BERT, GPT and Megatron Models for different NLP and dialog
  • system tasks using �PyTorch� Deep Learning Frameworks and performing NLP data wrangling
  • and tokenization
  • * Understanding of MLOps life cycle and experience with MLOps workflows & traceability and
  • versioning of datasets including knowhow of database management and queries (in SQL,
  • MongoDB etc)
  • * Experience using end-to-end MLOps platform such as Kube Flow, MLFlow, AirFlow
  • * Strong collaborative and interpersonal skills,specifically a proven ability to effectively guide
  • and influence within a dynamic matrix environment.

Required Skills

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