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We are looking for aGenerative AI Engineerwith 3+ years of hands-on experience in building AI-driven applications. The ideal candidate will have strong expertise inmachine learning, deep learning, and large language models (LLMs), with a passion for applying GenAI to solve real-world problems. You will collaborate with product, data science, and engineering teams to design, fine-tune, and deploy generative AI models at scale.
Design, fine-tune, and deployLLMs and other generative AI modelsfor production use cases.
Work withtransformer architectures(GPT, BERT, LLaMA, etc.) for text, image, or multimodal tasks.
Buildend-to-end pipelinesfor training, inference, and evaluation of AI models.
Implementprompt engineering, RAG (Retrieval-Augmented Generation), and model optimizationfor improved performance.
Integrate GenAI capabilities intoweb, mobile, or enterprise applications.
Leverage frameworks such asLangChain, Hugging Face, TensorFlow, PyTorch.
Collaborate with backend/frontend teams to developAPIs and servicesthat serve AI models.
Ensure AI solutions meetscalability, latency, and securityrequirements.
Research and stay updated on the latest advancements inGenerative AI, LLMOps, and ML infrastructure.
Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field.
4+ years of experiencein machine learning, NLP, or AI development.
Proficiency inPythonand libraries likePyTorch, TensorFlow, Hugging Face Transformers.
Solid understanding ofLLMs, embeddings, vector databases (Pinecone, Qdrant, Weaviate, FAISS).
Experience withRAG pipelines, fine-tuning, or prompt engineering.
Familiarity withcloud platforms(AWS, GCP, Azure) for ML deployment.
Strong knowledge ofAPIs, microservices, and containerization (Docker, Kubernetes).
Experience withLangChain / LangGraph LlamaIndexfor AI application orchestration.
Knowledge ofMLOps / LLMOps pipelines.
Exposure tomultimodal AI(text, image, speech).
Hands-on experience withvector search optimizations.
Contributions toopen-source AI projects.
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