AI Engineer
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The role
Design, implement, and scale LLM-based systems with a focus on optimization and MLOps.
Build robust backend APIs, deploy efficient model serving, and implement retrieval-augmented generation (RAG) pipelines.
Fine-tune foundation models using parameter-efficient methods (LoRA, QLoRA, adapters) for target domains.
Develop automated evaluation, monitoring, and testing pipelines to ensure quality, performance, and cost efficiency.
Collaborate with data engineering, product, and operations teams to deliver production-ready AI solutions at scale.
Utilize PyTorch, Transformers, LangChain, and tools like Docker, Kubernetes, and cloud ML services to ship results.
Build robust backend APIs, deploy efficient model serving, and implement retrieval-augmented generation (RAG) pipelines.
Fine-tune foundation models using parameter-efficient methods (LoRA, QLoRA, adapters) for target domains.
Develop automated evaluation, monitoring, and testing pipelines to ensure quality, performance, and cost efficiency.
Collaborate with data engineering, product, and operations teams to deliver production-ready AI solutions at scale.
Utilize PyTorch, Transformers, LangChain, and tools like Docker, Kubernetes, and cloud ML services to ship results.
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