Description

Fine-tune LLMs using techniques like LoRA and QLoRA
Evaluate and improve RAG (Retrieval-Augmented Generation) pipelines for groundedness, accuracy, and relevance
Apply transfer learning and transformer architectures in model development
Validate model accuracy and performance using appropriate metrics
Collaborate with product teams and communicate insights to senior leadership
Participate in problem-solving sessions and contribute innovative ideas
Maintain an experimental mindset and continuously explore new approaches
Identify and integrate relevant data sources to build meaningful datasets
Automate data collection and preprocessing for structured and unstructured data
Handle large-scale data to feed analytical and predictive models
Build and optimize machine learning and deep learning models, including NLP solutions

Requirements

Education & Experience :

Bachelors degree in a quantitative field (Computer Science, Engineering, Physics, Mathematics, Operations Research) or equivalent experience
3 - 5 years of hands-on experience in Gen AI and NLP
Prior experience in startups or high-growth environments is a plus

Technical Skills

Deep expertise in NLP techniques : text generation, sentiment analysis, NER, and language modeling
Hands-on experience with LLMs and RAG pipelines
Proficiency in neural network frameworks : TensorFlow, PyTorch
Familiarity with transformer architecture and transfer learning
Fluency in at least one programming language : Python, R, or Julia
Experience with Gen AI libraries : Hugging Face, OpenAI, etc.
Strong foundation in ML algorithms : supervised, unsupervised, reinforcement learning, Bayesian inference
Fine Tuning, Transfer Learning, Pytorch, Tensorflow

(ref:hirist.tech)

Interesting Job Opportunity: Generative AI Engineer - LLM

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