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Research & Development - AI Prompt Engineer Company Overview : We are Motive - the worlds leading provider of device management for mobile, fixed and IOT as well as managing the omni-channel customer experience which through its business logic drives actions, runs proactive care campaigns and improves customer satisfaction. Deployed by leading service providers worldwide, Motives device management and service management platform drive revenue, reduce customer care costs and automate each customer interaction. A relaunched brand with a long history and pedigree, at Motive we differentiate ourselves by creating innovative technical solutions, packaging them in ways that simplify operational complexity and time to market, and we never forget that we only succeed when our customers succeed. As a member of the Motive team, you will share a passion for being part of an exciting team of talented individuals, with a focus on building sustained long-term growth, and a fantastic place to work. Surrounded by individuals of exceptional ability and commitment, you will have the opportunity both to contribute to our continued business success, and to also invest in your own personal development. At Motive we hire only passionate team orientated people to join our business. Are you one of them? Position Summary: As a Research and Development AI Prompt Engineer, you will be at the forefront of creating and enhancing our software products. You will maximize the value of the R&D team’s delivery in research, design, prototyping, and development of new features and solutions. In this role, you will focus on developing, optimizing, and fine-tuning AI prompts for various natural language processing (NLP) and generative AI systems. You will work closely with software engineers to improve model outputs, refine AI understanding, and ensure the quality and accuracy of generated content. As an AI Prompt Engineer, you’ll play a key role in creating effective and efficient prompts that maximize the performance of AI models, particularly those focused on tasks such as anomaly detection, prediction, question answering, summarization, and more. Main Responsibility Areas: Prompt Design and Optimization Develop, test, and optimize natural language prompts for a variety of tasks, ensuring that AI models produce accurate, contextually relevant, and high-quality responses Experiment with different prompt engineering techniques, strategies, and styles to improve AI model outputs in various scenarios (e.g., anomaly detection, chatbot interactions, code generation, etc.) Analyze and refine existing prompts to ensure the desired AI model behavior AI Model Fine-tuning Collaborate with R&D and Professional Services software engineers to fine-tune pre-trained models using custom prompts for specific business requirements or user needs. Conduct prompt-based testing and validation to assess model performance and quality. Develop feedback loops to iteratively improve prompt designs based on model output quality. Performance Optimization: Analyze AI model outputs and fine tune prompts to improve accuracy and performance. Work closely with R&D software engineers to integrate prompt-engineered models into production systems and applications. Partner with product managers and UX/UI designers to understand user needs and ensure that AI-generated content aligns with user expectations and business goals. Document prompt engineering strategies, guidelines, and best practices. Maintain detailed records of model performance metrics and improvements over time. Provide regular updates to stakeholders on prompt optimization results and model performance. Stay up-to-date with the latest trends and techniques in AI, NLP, and prompt engineering. Create prototypes and proof-of-concept models to demonstrate the feasibility and potential of new ideas. Key Skills & Competencies: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Linguistics, AI, Data Science, or a related field. Advanced degrees and relevant certifications are a plus. Strong understanding of natural language processing (NLP) techniques and machine learning models (e.g., GPT, BERT, T5). Experience with AI prompt engineering, fine-tuning, and content generation tasks. Familiarity with large-scale pre-trained models, including transformers and generative models. Proficiency in programming languages such as Python, with a focus on libraries like Hugging Face, TensorFlow, PyTorch, or OpenAI’s API. Troubleshooting skills. Familiarity with AI platforms and cloud computing services (e.g., AWS, GCP, Azure). Expertise in Atlassian Jira and Confluence tools as well as Microsoft SharePoint Excellent verbal and written communication skills. Ability to articulate technical concepts to both technical and non-technical stakeholders. Ability to work effectively in a collaborative team environment. Strong interpersonal skills and a proactive attitude. Ability to quickly learn and apply new technologies. Flexibility to adapt to changing priorities and project requirements. Work Experience Requirements: Experience working with generative models such as GPT-3/4, BERT, or T5. Familiarity with conversational AI, chatbots, and interactive AI systems. Experience with data labeling, model evaluation, and data annotation. A strong portfolio showcasing previous work in prompt design or AI-driven NLP systems. Knowledge of AI ethics, bias mitigation, and content moderation techniques. Limitations and Disclaimer The above job description is meant to describe the general nature and level of work being performed; it should not be construed as an exhaustive list of all responsibilities, duties and skills required for the position. All job requirements are subject to possible modification to reasonably accommodate individuals with disabilities. Some requirements may exclude individuals who pose a direct threat or significant risk to the health and safety of themselves or other employees. This job description in no way states or implies that these are the only duties to be performed by the employee occupying this position. Employees will be required to follow any other job-related instructions and to perform other job-related duties requested by their manager.

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 5+ years of experience working with transformer-based models and NLP tasks , with a focus on text generation , summarization , question answering , classification , and similar tasks. Expertise in transformer models like GPT (Generative Pre-trained Transformer) , BERT (Bidirectional Encoder Representations from Transformers) , T5 (Text-to-Text Transfer Transformer) , RoBERTa , and similar models. 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 prompting Use of zero-shot , few-shot , and many-shot learning 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. Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, SpaCy, NLTK). Experience with transformer-based models (e.g., GPT, BERT, T5) for text generation tasks. 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

We are looking for Indias top 1% NLP Engineers for a unique job opportunity to work with the industry leaders Who can be a part of the community? We are looking for top-tier Natural Language Processing Engineers with experience in text analytics, LLMs, and speech processing If you have experience in this field then this is your chance to collaborate with industry leaders Whats in it for you? Pay above market standards The role is going to be contract based with project timelines from 2 12 months, or freelancing Be a part of Elite Community of professionals who can solve complex AI challenges Work location could be: Remote (Highly likely) Onsite on client location Deccan AIs Office: Hyderabad or Bangalore Responsibilities: Develop and optimize NLP models (NER, summarization, sentiment analysis) using transformer architectures (BERT, GPT, T5, LLaMA) Build scalable NLP pipelines for real-time and batch processing of large text data and optimize models for performance and deploy on cloud platforms (AWS, GCP, Azure) Implement CI/CD pipelines for automated training, deployment, and monitoring & integrate NLP models with search engines, recommendation systems, and RAG techniques Ensure ethical AI practices and mentor junior engineers Required Skills: Expert Python skills with NLP libraries (Hugging Face, SpaCy, NLTK) Experience with transformer-based models (BERT, GPT, T5) and deploying at scale (Flask, Kubernetes, cloud services) Strong knowledge of model optimization, data pipelines (Spark, Dask), and vector databases Familiar with MLOps, CI/CD (MLflow, DVC), cloud platforms, and data privacy regulations Nice to Have: Experience with multimodal AI, conversational AI (Rasa, OpenAI API), graph-based NLP, knowledge graphs, and A/B testing for model improvement Contributions to open-source NLP projects or a strong publication record What are the next steps? Register on our Soul AI website Our team will review your profile Clear all the screening rounds: Clear the assessments once you are shortlisted Profile matching and Project Allocation: Be patient while we align your skills and preferences with the available project Skip the Noise Focus on Opportunities Built for You! Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune,India