Data Scientist

Recode Solutions

3 - 8 years

7 - 11 Lacs

Chennai

Posted:1 day ago| Platform:

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Skills Required

Training Prototype Linux Coding Transformers Natural language processing Open source bash scripting Python Scripting

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Summary

We are looking for a hands-on DataScientist with deep expertise in NLP and Generative AI to help build andrefine the intelligence behind our agentic AI systems. You will be responsiblefor fine-tuning , prompt engineering , and evaluating LLMs that power our digital workers across real-world workflows.
Key Responsibilities

Fine-tune and evaluate LLMs(e.g., Mistral, LLaMA, Qwen) using frameworks like Unsloth , HuggingFace,and DeepSpeed

Develop high-quality promptsand RAG pipelines for few-shot and zero-shot performance

Analyze and curatedomain-specific text datasets for training and evaluation

Conduct performance and safetyevaluation of fine-tuned models

Collaborate with engineeringteams to integrate models into agentic workflows

Stay up to date with the latestin open-source LLMs and GenAI tools, and rapidly prototype experiments

Apply efficient training andinference techniques (LoRA, QLoRA, quantization, etc.)

Requirements
3+ years of experience in Natural Language Processing (NLP) and machinelearning applied to text

Strong coding skills in python

Hands-on experience fine-tuning LLMs (e.g., LLaMA, Mistral,Falcon, Qwen) using frameworks like Unsloth , HuggingFace Transformers , PEFT , LoRA , QLoRA , bitsandbytes

Proficient in PyTorch (preferred) or TensorFlow , withexperience in writing custom training/evaluation loops

Experience in dataset preparation , tokenization (e.g., Tokenizer,tokenizers), and formatting for instruction tuning (ChatML, Alpaca, ShareGPTformats)

Familiarity with retrieval-augmented generation (RAG) using FAISS , Chroma , Weaviate , or Qdrant

Strong knowledge of prompt engineering , few-shot/zero-shotlearning , chain-of-thought prompting , and function-callingpatterns

Exposure to agentic AI frameworks like CrewAI , Phidata , LangChain , LlamaIndex , or AutoGen

Experience with GPU-accelerated training/inference and librarieslike DeepSpeed , Accelerate , Flash Attention , Transformersv2 , etc.

Solid understanding of LLM evaluation metrics (BLEU, ROUGE,scripting for training pipelines , data curation , or evaluationworkflows
Nice to Haves

Experience in Linux (Ubuntu)

Terminal/Bash Scripting

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