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Jr. Data Scientist
2 weeks ago
Job Description:
We are seeking a talented and driven
Generative AI (GenAI) Engineer
with
2–6 years of experience
to join our growing AI innovation team in
Ahmedabad or Pune
. In this role, you'll work on cutting-edge projects involving
Large Language Models (LLMs)
and
Small Language Models (SLMs)
, with a focus on
Retrieval-Augmented Generation (RAG)
,
contextual similarity
, and transformer-based architectures like
BERT
.
Key Responsibilities:
- Develop and optimize
RAG pipelines
, including modules for sorting, filtering, ranking, and
re-ranking
of retrieved data. - Work with both
closed-source and open-source LLMs/SLMs
to solve real-world business problems. - Implement
Chain of Thought (CoT)
reasoning to enhance model interpretability and output accuracy. - Design and apply
contextual similarity
,
graph-based RAG
, and
corrective RAG
techniques to improve model relevance and trustworthiness. - Fine-tune and utilize
BERT
and other transformer models for embeddings, classification, and NLP tasks. - Develop scalable APIs and microservices using
Flask
to integrate GenAI functionality into applications. - Research and prototype emerging GenAI capabilities for integration into existing systems.
- Collaborate cross-functionally with product managers, ML engineers, and software developers to deliver robust GenAI solutions.
Required Skills & Qualifications:
- 2–6 years of hands-on experience in
Python
and AI/ML development. - Deep understanding of
LLMs and SLMs
, including implementation and integration strategies. - Experience with
Retrieval-Augmented Generation (RAG)
architecture and retrieval optimization techniques. - Proficiency in
contextual similarity
, vector-based search, and semantic relevance models. - Strong understanding of
Chain of Thought (CoT)
prompting and reasoning techniques. - Experience working with
Graph RAG
and
Corrective RAG
for enhanced model accuracy. - Familiarity with
BERT
and other transformer-based models for NLP use cases. - Practical experience building APIs using
Flask
or similar frameworks.
Preferred Qualifications:
- Experience with
vector databases
(e.g., FAISS, Pinecone, Weaviate). - Familiarity with
LangChain
,
Haystack
, or LLM orchestration tools. - Experience deploying GenAI solutions on cloud platforms (AWS, Azure, GCP).
- Knowledge of prompt engineering, tokenization, and conversational memory.