Job Description: AI/ML Research Engineer with LangChain and LLM
Expertise
We are seeking a talented AI/ML Research Engineer with expertise in transformer
architectures large language models (LLMs) and LangChain to join our innovative team. The ideal candidate will have a strong understanding of both the theoretical and practical aspects of LLMs and experience integrating various models into dynamic systems. You will work on cuttingedge AI projects contributing to the development of questionanswering systems conversational agents and document analysis tools while ensuring seamless API integration.
Key Responsibilities:
LLM Expertise:
Develop and finetune transformerbased models (e.g. GPT BERT etc.)
Implement tokenization and embedding strategies to optimize model performance.
Utilize prompt engineering techniques to design effective interactions with
LLMs.
Apply finetuning and transfer learning to enhance existing models.
Explore and implement various LLM architectures to solve realworld problems.
LangChain Integration:
Build and deploy systems using LangChain s core concepts such as Chains Agents and Memory.
Integrate diverse LLMs into LangChain workflows to create custom agents and tools.
Implement conversational memory to enable dynamic and contextaware interactions.
Develop document analysis and retrieval systems using LangChain modules.
Construct advanced questionanswering systems leveraging LangChain and
LLMs.
API Development and Integration:
Design and implement APIs for seamless integration of AI models with external
applications.
Work with crossfunctional teams to integrate research outcomes into production systems.
Ensure APIs enable smooth interaction with external systems databases and thirdparty tools.
Qualifications:
Strong understanding of transformer architecture and LLM types (e.g. GPT BERT
etc.)
Handson experience with LangChain s modules and building tools within the
framework.
Proficiency in tokenization embeddings and designing models for prompt
engineering.
Experience with finetuning transfer learning and model optimization.
API development and integration experience in Python along with frameworks such
as FastAPI Flask or Django.
Experience with ML frameworks like TensorFlow PyTorch or Hugging Face
Transformers.
Strong programming skills in Python and proficiency in creating scalable ML pipelines.
Familiarity with machine learning fundamentals deep learning techniques and model evaluation.
Excellent problemsolving and communication skills with an ability to work
crossfunctionally
Bonus Skills:
Experience working with LangChain to build custom conversational agents.
Understanding of document retrieval and knowledgebased systems.
Familiarity with deploying LLMs into production and optimizing performance.
Join us and be part of a team driving innovation at the intersection of AI research LLMs and LangChain development! Apply today to contribute to pioneering projects and advance the future of AI.
api development,artificial intelligence,integration,langchain modules,tokenization,deep learning techniques,api,transfer learning,ml,embeddings,python programming,machine learning fundamentals,transformer,model evaluation,research,llm types,models,transformer architecture,ml frameworks,fine-tuning,prompt engineering
AI ML Engineer Research Focus
