Senior Machine Learning Engineer
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Le poste
Design, develop, and deploy scalable ML and NLP solutions, focusing on transformer-based models and LLMs for real-world tasks such as summarization, question answering, semantic search, and chatbots.
Build scalable data pipelines and model training workflows, conduct rigorous evaluation, and continuously monitor deployed models to ensure reliability and accuracy over time.
Design, fine-tune, and deploy LLMs (e.g., LLaMA, Mistral) and implement retrieval-augmented generation pipelines using vector databases like FAISS, Weaviate, Pinecone, or Milvus.
Develop efficient model serving infrastructure with ONNX, TensorRT, DeepSpeed, or vLLM and optimize inference latency, throughput, and cost across cloud and edge environments.
Collaborate with cross-functional teams to translate business requirements into ML solutions, mentor junior engineers, and contribute to knowledge sharing and documentation.
Stay current with research, apply best practices in MLOps, and emphasize reproducibility and security-conscious development in production-ready systems.
Build scalable data pipelines and model training workflows, conduct rigorous evaluation, and continuously monitor deployed models to ensure reliability and accuracy over time.
Design, fine-tune, and deploy LLMs (e.g., LLaMA, Mistral) and implement retrieval-augmented generation pipelines using vector databases like FAISS, Weaviate, Pinecone, or Milvus.
Develop efficient model serving infrastructure with ONNX, TensorRT, DeepSpeed, or vLLM and optimize inference latency, throughput, and cost across cloud and edge environments.
Collaborate with cross-functional teams to translate business requirements into ML solutions, mentor junior engineers, and contribute to knowledge sharing and documentation.
Stay current with research, apply best practices in MLOps, and emphasize reproducibility and security-conscious development in production-ready systems.
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