Principal Machine Learning Researcher

Role Overview You will lead the development and deployment of production-level NLP and machine learning systems running on high-performance bare-metal infrastructure. You should have strong expertise in deep learning, NLP pipelines, large-scale data processing, and AI infrastructure engineering. Collaboration with AI engineers, product teams, and software developers is essential to transform healthcare and enterprise data into intelligent AI-powered solutions. Key Responsibilities - Design, develop, and deploy production-grade NLP systems and AI pipelines - Build scalable machine learning and deep learning models for healthcare and enterprise applications - Work directly with bare-metal and on-premise infrastructure for optimized AI performance - Develop and optimize text-processing pipelines, vector systems, embeddings, and LLM workflows - Build robust data ingestion, preprocessing, and model-serving architectures - Fine-tune and optimize transformer-based models using frameworks like PyTorch and TensorFlow - Collaborate with cross-functional teams to translate business and healthcare requirements into scalable AI solutions - Improve model performance, inference speed, reliability, and infrastructure efficiency - Contribute to AI research, experimentation, and next-generation product innovation Qualification Required Must-Have Technical Skills: - 5+ years of hands-on experience in Data Science, Machine Learning, or AI Engineering - Strong expertise in Python programming - Deep experience with: PyTorch, TensorFlow, NLP frameworks, and transformer models - Strong understanding of: LLMs / Generative AI, Embeddings & Vector Databases, Text-processing pipelines, Deep Learning architectures - Experience with Docker and containerized deployments - Hands-on exposure to on-premise / bare-metal infrastructure environments - Strong knowledge of scalable ML pipelines and production deployment practices - Experience working with large datasets and distributed processing systems Preferred Qualifications: - Experience in healthcare AI or medical technology systems - Exposure to RAG pipelines, multi-agent AI systems, or multimodal AI - Familiarity with Kubernetes, GPU optimization, and inference acceleration - Experience in MLOps and model monitoring systems If you are passionate about building large-scale AI systems and production-grade NLP infrastructure, NUVO AI offers you the opportunity to work on cutting-edge AI and healthcare innovation in a collaborative and innovation-driven culture. Role Overview You will lead the development and deployment of production-level NLP and machine learning systems running on high-performance bare-metal infrastructure. You should have strong expertise in deep learning, NLP pipelines, large-scale data processing, and AI infrastructure engineering. Collaboration with AI engineers, product teams, and software developers is essential to transform healthcare and enterprise data into intelligent AI-powered solutions. Key Responsibilities - Design, develop, and deploy production-grade NLP systems and AI pipelines - Build scalable machine learning and deep learning models for healthcare and enterprise applications - Work directly with bare-metal and on-premise infrastructure for optimized AI performance - Develop and optimize text-processing pipelines, vector systems, embeddings, and LLM workflows - Build robust data ingestion, preprocessing, and model-serving architectures - Fine-tune and optimize transformer-based models using frameworks like PyTorch and TensorFlow - Collaborate with cross-functional teams to translate business and healthcare requirements into scalable AI solutions - Improve model performance, inference speed, reliability, and infrastructure efficiency - Contribute to AI research, experimentation, and next-generation product innovation Qualification Required Must-Have Technical Skills: - 5+ years of hands-on experience in Data Science, Machine Learning, or AI Engineering - Strong expertise in Python programming - Deep experience with: PyTorch, TensorFlow, NLP frameworks, and transformer models - Strong understanding of: LLMs / Generative AI, Embeddings & Vector Databases, Text-processing pipelines, Deep Learning architectures - Experience with Docker and containerized deployments - Hands-on exposure to on-premise / bare-metal infrastructure environments - Strong knowledge of scalable ML pipelines and production deployment practices - Experience working with large datasets and distributed processing systems Preferred Qualifications: - Experience in healthcare AI or medical technology systems - Exposure to RAG pipelines, multi-agent AI systems, or multimodal AI - Familiarity with Kubernetes, GPU optimization, and inference acceleration - Experience in MLOps and model monitoring systems If you are passionate about building large-scale AI systems and production-grade NLP infrastructure, NUVO AI offers you the opportunity to work on cutting-edge AI and healthcare i