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LLM Engineer - Data Modeling Job Opening In India, India – Now Hiring Follex Technology


Job description

<p><p><b>Position : Senior LLM Engineer</b><br/><br/><b>Experience : Overall 7+Yrs</b><br/><br/><b>Relevant : 4+Yrs</b><br/><br/><b>Location : Hyderabad(Onsite)</b><br/><br/><b>Notice Period : Immediate Joiner</b><br/><br/><b>Key Responsibilities :</b></p><p><p><b><br/></b></p>- Model Expertise : Work with transformer models (GPT, BERT, T5, RoBERTa, etc.) across NLP tasks including text generation, summarization, classification, and translation.<br/><br/></p><p>- Model Fine-Tuning : Fine-tune pre-trained models on domain-specific datasets to optimize for summarization, text generation, question answering, and related tasks.<br/><br/></p><p>- Prompt Engineering : Design, test, and iterate on contextually relevant prompts to guide model outputs for desired performance.<br/><br/></p><p>- Instruction-Based Prompting : Implement and refine instruction-based prompting strategies to achieve contextually accurate results.<br/><br/></p><p>- Learning Approaches : Apply zero-shot, few-shot, and many-shot learning methods to maximize model performance without extensive retraining.<br/><br/></p><p>- Reasoning Enhancement : Leverage Chain-of-Thought (CoT) prompting for structured, step-by-step reasoning in complex tasks.<br/><br/></p><p>- Model Evaluation : Evaluate model performance using BLEU, ROUGE, and other relevant metrics; identify opportunities for improvement.<br/><br/></p><p>- Deployment : Deploy trained and fine-tuned models into production environments, </p><p>integrating with real-time systems and pipelines.</p><p><br/></p><p>- Bias & Reliability : Identify, monitor, and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs.<br/><br/></p><p>- Collaboration : Work closely with cross-functional teams (data scientists, engineers, product managers) to design scalable and efficient NLP-driven solutions.<br/><br/><b>Must-Have Skills :</b></p><p><p><b><br/></b></p>- 7+ years of overall experience in software/AI development with at least 2+ years in transformer-based NLP models.<br/><br/></p><p>- 4+ years of hands-on expertise with transformer architectures (GPT, BERT, T5, RoBERTa, etc.).<br/><br/></p><p>- Strong understanding of attention mechanisms, self-attention layers, tokenization, embeddings, and context windows.<br/><br/></p><p>- Proven experience in fine-tuning pre-trained models for NLP tasks (summarization, classification, text generation, translation, Q&A).<br/><br/></p><p>- Expertise in prompt engineering, including zero-shot, few-shot, many-shot learning, and </p><p>prompt template creation.<br/><br/></p><p>- Experience with instruction-based prompting and Chain-of-Thought prompting for reasoning tasks.<br/><br/></p><p>- Proficiency in Python and NLP libraries/frameworks such as Hugging Face Transformers, </p><p>SpaCy, NLTK, PyTorch, TensorFlow.<br/><br/></p><p>- Strong knowledge of model evaluation metrics (BLEU, ROUGE, perplexity, etc.).<br/><br/></p><p>- Experience in deploying models into production environments.<br/><br/></p><p>- Awareness of bias, hallucinations, and limitations in LLM outputs.<br/><br/><p><b>Good to Have :</b></p><p><br/></p>- Experience with LLM observability tools and monitoring pipelines.<br/><br/></p><p>- Exposure to cloud platforms (AWS, GCP, Azure) for scalable model deployment.<br/><br/></p><p>- Knowledge of MLOps practices for model lifecycle management.</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your LLM Engineer Potential: Insight & Career Growth Guide


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The Work Culture

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2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying India laws and regulations

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The average salary range for a varies, but the pay scale is rated "Standard" in India. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for LLM Engineer Data Modeling typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Follex Technology interview tips for LLM Engineer   Data Modeling

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Before the Interview:

Research: Learn about the Follex Technology's mission, values, products, and the specific job requirements and get further information about

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Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

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Follow Up: Send a thank-you email to the interviewer within 24 hours.

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Final Thought:

To prepare for your LLM Engineer Data Modeling interview at Follex Technology, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Follex Technology's products or services and be prepared to discuss how you can contribute to their success.

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