GEN AI

Experience: 4+ years of experience in AI and machine learning Expertise in Python: Demonstrable experience with Python, including its data science and AI libraries such as TensorFlow, PyTorch, spaCy, and GPT (OpenAI). Familiarity with other programming languages such as Java or C++ is a plus. Azure OpenAI and Cloud Services: Hands-on experience with Azure OpenAI services, and a good understanding of other Azure services such as Azure Machine Learning, Azure Functions, and Azure Logic Apps for integrating AI capabilities. LLM and NLP Techniques: Deep understanding of Natural Language Processing (NLP) techniques, including tokenization, sentiment analysis, entity recognition, and especially the mechanics and applications of Large Language Models (LLMs). Creative Prompt Design: Ability to craft and refine prompts that effectively guide LLMs in producing desired textual outputs. This includes understanding different prompt types, such as zero-shot, few-shot, and chain-of-thought prompting. Strong programming skills in Python and familiarity with AI development tools and libraries. Should have hands-on experience in deploying at least one end to end GenAI project Knowledge of AI model training, fine-tuning, and deployment processes Excellent problem-solving and analytical skills Effective communication and interpersonal skills Qualification We are seeking skilled LLM Engineers with 5 to 8 years of experience to design, fine-tune, and implement large language model (LLM)-based solutions for an AI integration project. This role involves developing AI-driven functionalities tailored for Salesforce CRM and service ticketing platforms using Azure OpenAI and OpenAI technologies. Key Responsibilities: Develop and deploy LLM-based solutions for AI integration into Salesforce and service ticketing systems. Fine-tune pre-trained language models (e.g., GPT) to align with business requirements and enhance application performance. Collaborate with architects and stakeholders to implement generative AI-driven solutions for workflow automation and customer support. Ensure optimized performance and accuracy of LLMs for use cases such as ticket categorization, routing, and customer interaction. Design and implement scalable, secure, and compliant LLM-based architectures. Stay updated on advancements in AI/ML and LLM technologies and apply innovative techniques to solve business challenges. Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or related fields. 5 to 8 years of experience in software development or machine learning, with strong exposure to LLMs and generative AI models. Hands-on experience with Azure OpenAI, OpenAI APIs (e.g., GPT models), and their integration into enterprise systems. Proficiency in programming languages such as Python, with a focus on NLP libraries and ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Strong understanding of data preprocessing, model training, and optimization techniques for large-scale applications. Preferred Skills: Experience integrating LLM-based solutions with Salesforce and service ticketing platforms. Knowledge of cloud deployment and automation practices using tools like Docker, Kubernetes, or Azure DevOps. Familiarity with API development and integration for real-time AI functionalities. Understanding of data governance, security, and compliance standards in AI implementations