
Generative AI Engineer
2 days ago
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.
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