Develop and deploy generative AI solutions and LLMs. Build innovative AI applications and ML pipelines.
Responsibilities
Design and implement generative AI models for text, code, and multimodal applications; fine-tune, optimize, and deploy large language models (GPT, Claude, Llama, etc.); develop training pipelines for custom generative models and foundation model adaptation; build robust ML applications, APIs, and services using Python and ML frameworks; create and optimize prompts for various LLM applications; implement evaluation frameworks for generative AI model performance and safety; deploy and monitor ML models in production environments; stay current with latest GenAI research; build data preprocessing and feature engineering pipelines; collaborate with product, engineering, and data science teams.
Requirements
Total Experience: 6-8 years. Required: Deep expertise in ML algorithms, neural networks, and model optimization; hands-on experience with GANs, VAEs, diffusion models, and transformer architectures; proficiency in working with LLMs, fine-tuning, and deployment strategies; expert-level Python programming with ML libraries (PyTorch, TensorFlow, Hugging Face, Lang Chain); experience with model versioning, monitoring, and production deployment; knowledge of AWS, Azure, GCP ML services and GPU computing.
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