Lead Generative AI Engineer - LLM/NLP (8-12 yrs)

Job Description :

We are looking for a highly skilled Generative AI Engineer to join our team and drive the development of innovative AI models and applications. The ideal candidate will have deep expertise in Large Language Models (LLMs), with a focus on prompt engineering, fine-tuning, and grounding AI responses. You will be responsible for optimizing AI behavior, enabling chat completions, incorporating function calling, and utilizing retrieval-augmented generation (RAG) to provide more accurate and context-aware responses. Additionally, familiarity with OpenAI APIs and its features is crucial for this role.

Key Responsibilities :

- Prompt Engineering & Fine-tuning : Design and optimize prompts to ensure high-quality, relevant, and contextually accurate outputs from Large Language Models (LLMs). Fine-tune pre-trained models for specific tasks or domains, ensuring grounding and relevance in responses.

- LLM Patterns & Understanding : Analyze the behavior of LLMs, identifying patterns and biases to improve performance and reduce undesired outcomes. Develop strategies for model adjustments to enhance coherence and accuracy.

- Chat Completions : Build and improve systems to generate seamless, context-aware chat completions for a variety of use cases, ensuring natural and engaging conversations.

- Function Calling Integration : Integrate function calling capabilities into LLMs, enabling models to trigger real-world actions (such as querying databases or triggering APIs) based on user input.

- Retrieval-Augmented Generation (RAG) : Implement and optimize RAG techniques to pull in external knowledge (such as documents, APIs, or databases) and incorporate it into generative AI responses for more accurate and informed answers.

- OpenAI API & Feature Integration : Leverage OpenAI APIs to develop, deploy, and maintain AI-powered applications. Stay updated on the latest OpenAI features and implement them effectively to enhance model capabilities.

- Model Evaluation & Testing : Continuously evaluate models, ensuring outputs meet quality standards and adhere to ethical guidelines. Perform A/B testing, debugging, and iterative improvements on fine-tuned models.

- Collaboration : Work alongside data scientists, machine learning engineers, and product teams to integrate AI-driven solutions and optimize user-facing applications.

- Documentation & Knowledge Sharing : Maintain comprehensive documentation on prompt engineering strategies, fine-tuning processes, and implementation guidelines. Share best practices with the team to enhance overall development efficiency.

- AI Ethics : Ensure AI models are developed and deployed ethically, reducing the risk of biases, harmful outputs, and ensuring safety and fairness.

Qualifications :

- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, or a related field.

- 3+ years of experience working with Generative AI and Large Language Models (LLMs).

- Proficiency in prompt engineering techniques and optimizing AI behavior and output.

- Experience with fine-tuning models on specific datasets or use cases.

- Deep understanding of LLM patterns, strengths, weaknesses, and how to manipulate their responses effectively.

- Hands-on experience with chat completions, function calling, and integrating external knowledge using retrieval-augmented generation (RAG).

- Extensive experience working with OpenAI APIs (e.g., GPT-3, GPT-4) and integrating OpenAI features into applications.

- Strong proficiency in Python, with experience using libraries like Transformers, Hugging Face, and TensorFlow.

- Familiarity with NLP techniques and natural language processing pipelines.

- Strong analytical and problem-solving skills, with an ability to troubleshoot and optimize AI models.

- Excellent communication skills for documenting processes and collaborating with cross-functional teams.

Preferred Skills :

- Experience with other transformer models (e.g., T5, BERT).

- Experience with cloud platforms (AWS, Azure, Google Cloud) for model deployment and scaling.

- Familiarity with containerization and deployment tools like Docker and Kubernetes.

- Understanding of AI ethics, model interpretability, and bias mitigation.

- Prior work in building conversational agents or chatbot frameworks is a plus.

- Experience with AI-driven applications in real-world environments.

Why Join Us?

- Work on groundbreaking projects at the intersection of AI, NLP, and Generative Models.

- Collaborate with an experienced team of AI engineers and data scientists.

- Access to the latest technologies and tools in the AI space.

- Competitive salary and benefits.

- Opportunities for professional growth and career advancement.