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LLM Engineer/4-8 Years/ Hyderabad.
LLM Engineer/4-8 Years/ Hyderabad.
InRhythm Solutions's logo

LLM Engineer/4-8 Years/ Hyderabad.

Naveen Kumar's profile picture
Posted by Naveen Kumar
4 - 8 yrs
₹10L - ₹20L / yr
Hyderabad
Skills
Large Language Models (LLM)

Key Responsibilities:

  • Develop and fine-tune large language models for diverse applications.
  • Implement and optimize LLMs to create efficient, scalable solutions.
  • Build intelligent agents that utilize LLMs to interact and perform complex analytical tasks.
  • Collaborate with cross-functional teams to integrate LLM technology into our products and services.
  • Conduct research to stay ahead of the latest trends and advancements in generative AI and machine learning.
  • Document and present model development processes and results for stakeholders.


Required Qualifications:

  • 4-8 years of experience in machine learning, specifically with generative AI and large language models.
  • Strong proficiency in Python and familiarity with AI and ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
  • Experience in fine-tuning LLMs and deploying AI models in a production environment.
  • Proven ability to design and implement AI agents using LLMs.
  • Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment.
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About InRhythm Solutions

Founded :
2005
Type :
Product
Size :
20-100
Stage :
Profitable

About

N/A

Company social profiles

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Shubham Vishwakarma's profile image

Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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