Generative AI Engineer

Description :

Key Responsibilities :

- Design, build, and deploy Generative AI models using frameworks like LangChain, Hugging Face, OpenAI APIs, and Vertex AI.

- Fine-tune and optimize Large Language Models (LLMs) such as GPT, LLaMA, Falcon, or Claude for custom applications.

- Develop and implement machine learning pipelines for data preparation, model training, evaluation, and deployment.

- Collaborate with cross-functional teams including data scientists, ML engineers, and software developers to integrate AI models into products and systems.

- Work on NLP/NLU tasks such as summarization, classification, and conversational AI.

- Conduct experiments to evaluate model performance, scalability, and latency.

- Implement MLOps best practices for version control, CI/CD, and model monitoring.

- Research and experiment with state-of-the-art Generative AI techniques, keeping up with industry trends.

- Develop and maintain technical documentation for model architectures, APIs, and deployment pipelines.

Required Skills & Experience :

- Strong programming skills in Python, with experience in TensorFlow, PyTorch, Hugging Face Transformers, LangChain, or similar frameworks.

- Practical knowledge of Prompt Engineering, RAG (Retrieval-Augmented Generation), and LLM fine-tuning.

- Experience working with vector databases (e.g., Pinecone, FAISS, Chroma) and embedding models.

- Proficiency in NLP, computer vision, or multimodal AI concepts.

- Hands-on experience deploying models on cloud platforms (AWS, Azure, GCP).

- Understanding of data preprocessing, tokenization, and model evaluation metrics.

- Familiarity with API integration, containerization (Docker), and version control (Git).

- Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications :

- Certifications in Generative AI / Machine Learning / Cloud AI tools.