Job Description

About Prismforce

Prismforce is a Vertical SaaS company revolutionizing the Talent Supply Chain for global Technology,
R&D/Engineering, and IT Services companies. Our AI-powered product suite enhances business
performance by enabling operational flexibility, accelerating decision-making, and boosting
profitability. Our mission is to become the leading industry cloud/SaaS platform for tech services and
talent organizations worldwide.
We're looking for a passionate and curious Generative AI Engineer to join our team in Bangalore.
You'll work on cutting-edge NLP and ML projects, leveraging large language models (LLMs) and
advanced deep learning techniques to solve complex business challenges.
:
Role: Gen AI Engineering
Reporting to: Data Scientist
Location: Bangalore
Exp: 1-4 Years

Role Type : Contract 1 year

Key Responsibilities
? 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
? Bachelor's degree in a quantitative field (Computer Science, Engineering, Physics,
Mathematics, Operations Research) or equivalent experience
? 1-4 years of hands-on experience in Gen AI and NLP
? Prior experience in startups or high-growth environments is a plus

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* 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, TensorflowAnalytical