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About the role
You will be responsible for spearheading the development of advanced AI solutions, managing a multidisciplinary team of AI engineers and data scientists, and overseeing the implementation of machine learning and large language model (LLM) initiatives. Your strategic role will involve shaping the AI roadmap to ensure the delivery of high-impact models that enhance outcomes and operational efficiency of the product. Key Responsibilities: - AI/ML Product Development: Oversee the design, development, and deployment of machine learning, deep learning, and large language models (LLMs), including multimodal AI systems. - Team Management: Build, mentor, and lead a high-performing team of data scientists, AI researchers, and ML engineers. Foster a culture of innovation and technical excellence. - R&D and Innovation: Drive applied research in areas like medical imaging, predictive analytics, and clinical decision support. Guide exploration of novel algorithms and AI approaches. - Data Strategy & Governance: Ensure best practices in data preprocessing, cleaning, and analysis. Collaborate with data engineering for robust pipelines and scalable infrastructure. - Model Evaluation & Ethics: Champion rigorous model validation, monitoring, and explainability. Ensure ethical AI practices, especially in sensitive healthcare applications. - Thought Leadership: Stay abreast of AI/ML advancements and represent the company in conferences, publications, and key industry forums. Technical Skills: - Programming Skills: Proficiency in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, and Hugging Face. Familiarity with TensorRT and NVIDIA Triton Server is a plus. - Model Expertise: Deep experience with Convolutional Neural Networks (CNNs), diffusion models, transformers, as well as segmentation, object detection, and classification models, including CLIP or similar models. - Multimodal Proficiency: Strong knowledge and experience with large language models (LLMs) and multimodal AI approaches. - Algorithmic Understanding: Comprehensive understanding of a wide array of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning techniques. You should possess 8 years of experience in data science, AI/ML, or applied research, with at least 3 years in a leadership or managerial role. A proven track record of deploying AI models into production, preferably in healthcare, medical imaging, or life sciences is required. A Bachelors or Masters in Computer Science, Data Science, Engineering, or a related field is necessary, with a PhD being preferred. You will be responsible for spearheading the development of advanced AI solutions, managing a multidisciplinary team of AI engineers and data scientists, and overseeing the implementation of machine learning and large language model (LLM) initiatives. Your strategic role will involve shaping the AI roadmap to ensure the delivery of high-impact models that enhance outcomes and operational efficiency of the product. Key Responsibilities: - AI/ML Product Development: Oversee the design, development, and deployment of machine learning, deep learning, and large language models (LLMs), including multimodal AI systems. - Team Management: Build, mentor, and lead a high-performing team of data scientists, AI researchers, and ML engineers. Foster a culture of innovation and technical excellence. - R&D and Innovation: Drive applied research in areas like medical imaging, predictive analytics, and clinical decision support. Guide exploration of novel algorithms and AI approaches. - Data Strategy & Governance: Ensure best practices in data preprocessing, cleaning, and analysis. Collaborate with data engineering for robust pipelines and scalable infrastructure. - Model Evaluation & Ethics: Champion rigorous model validation, monitoring, and explainability. Ensure ethical AI practices, especially in sensitive healthcare applications. - Thought Leadership: Stay abreast of AI/ML advancements and represent the company in conferences, publications, and key industry forums. Technical Skills: - Programming Skills: Proficiency in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, and Hugging Face. Familiarity with TensorRT and NVIDIA Triton Server is a plus. - Model Expertise: Deep experience with Convolutional Neural Networks (CNNs), diffusion models, transformers, as well as segmentation, object detection, and classification models, including CLIP or similar models. - Multimodal Proficiency: Strong knowledge and experience with large language models (LLMs) and multimodal AI approaches. - Algorithmic Understanding: Comprehensive understanding of a wide array of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning techniques. You should possess 8 years