Senior LLM Engineer

Senior LLM Engineer

About Company :

Nomiso is a product and services engineering company. We are a team of Software Engineers, Architects, Managers, and Cloud Experts with expertise in Technology and Delivery Management.

Our mission is to Empower and Enhance the lives of our customers, through efficient solutions for their complex business problems.

At Nomiso we encourage entrepreneurial spirit - to learn, grow and improve. A great workplace, thrives on ideas and opportunities. That is a part of our DNA. We’re in pursuit of colleagues who share similar passions, are nimble and thrive when challenged. We offer a positive, stimulating and fun environment – with opportunities to grow, a fast-paced approach to innovation, and a place where your views are valued and encouraged.

We invite you to push your boundaries and join us in fulfilling your career aspirations!

What You Can Expect from Us :

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers. You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview :

We are seeking an experienced NLP & LLM Specialist to join our team. The ideal candidate will have deep expertise in working with transformer-based models, including GPT, BERT, T5, RoBERTa , and similar models. This role requires experience in fine-tuning these pre-trained models on domain-specific tasks, as well as crafting and optimizing prompts for natural language processing tasks such as text generation, summarization, question answering, classification, and translation. The candidate should be proficient in Python and familiar with NLP libraries like Hugging Face, SpaCy , and NLTK , with a solid understanding of model evaluation metrics.

Roles and Responsibilities :

Model Expertise : Work with transformer models such as GPT , BERT , T5 , RoBERTa , and others for a variety of NLP tasks, including text generation, summarization, classification, and translation.

Model Fine-Tuning : Fine-tune pre-trained models on domain-specific datasets to improve performance for specific applications such as summarization, text generation, and question answering.

Prompt Engineering : Craft clear, concise, and contextually relevant prompts to guide transformer-based models towards generating desired outputs for specific tasks. Iterate on prompts to optimize model performance.

Instruction-Based Prompting : Implement instruction-based prompting to guide the model toward achieving specific goals, ensuring that the outputs are contextually accurate and aligned with task objectives.

Zero-shot, Few-shot, Many-shot Learning : Utilize zero-shot , few-shot , and many-shot learning techniques to improve model performance without the need for full retraining.

Chain-of-Thought (CoT) Prompting : Implement Chain-of-Thought (CoT) prompting to guide models through complex reasoning tasks, ensuring that the outputs are logically structured and provide step-by-step explanations.

Model Evaluation : Use evaluation metrics such as BLEU , ROUGE , and other relevant metrics to assess and improve the performance of models for various NLP tasks.

Model Deployment : Support the deployment of trained models into production environments and integrate them into existing systems for real-time applications.

Bias Awareness : Be aware of and mitigate issues related to bias , hallucinations , and knowledge cutoffs in LLMs, ensuring high-quality and reliable outputs.

Collaboration : Collaborate with cross-functional teams including engineers, data scientists, and product managers to deliver efficient and scalable NLP solutions.

Must Have Skill

Overall 7+ years with at least 2+ years of experience working with transformer-based models and NLP tasks , with a focus on text generation , summarization , question answering , classification , and similar tasks.

Relevant 4+ Years, Expertise in transformer (decoder) models like GPT (Generative Pre-trained Transformer) , Claude based models , and similar models, for generative tasks.

Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text.

Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation , summarization , question answering , classification , and translation .

Familiarity with concepts like attention mechanisms , context windows , tokenization , and embedding layers .

Awareness of biases , hallucinations , and knowledge cutoffs that can affect LLM performance and output quality.

Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs.

Experience in instruction-based, zero-shot , few-shot , Chain-of-though and ReACT prompting techniques for maximizing model performance without retraining.

Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results.

Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs.

Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, SpaCy, NLTK).

Experience in training, fine-tuning, and deploying machine learning models in an NLP context.

Understanding of model evaluation metrics (e.g., BLEU, ROUGE)

Qualification :

BE / B.Tech or Equivalent degree in Computer Science or related field.

Excellent communication skills in English, both verbal and written

Location :

Hyderabad / Bangalore

Website :