Senior AI Scientist

March 24

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Artisight

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Artisight is a healthcare technology company that offers a Smart Hospital Virtual Nursing Platform designed to optimize clinical workflows and improve patient care. Their platform uses computer vision, multi-sensor networks, and artificial intelligence to automate tasks, enhance communication, and provide real-time actionable data. Artisight's solutions aim to reduce clinician workload, improve patient safety, and increase operational efficiency. The company is focused on addressing the current challenges in healthcare, such as health equity and patient access, by creating a more human-centered and future-ready healthcare environment.

smarthospitals • computervision • healthcareAI

51 - 200 employees

⚕️ Healthcare Insurance

🤖 Artificial Intelligence

☁️ SaaS

💰 $42M Series B on 2024-01

📋 Description

•Collaborate with product, AI, and engineering teams to develop and deploy state-of-the-art AI models for real-world healthcare applications. •Design, train, fine-tune, and optimize foundation models, including large language models (LLMs) and vision-language models (VLMs). •Implement and scale generative AI solutions, ensuring robustness, efficiency, and ethical AI considerations in production systems. •Contribute to the architecture of Artisight’s AI platform, ensuring seamless integration of generative AI capabilities. •Lead and mentor a team of AI scientists and engineers, fostering innovation and technical excellence. •Stay at the forefront of AI advancements, evaluating and integrating emerging technologies in generative AI and multimodal learning.

🎯 Requirements

•B.S./M.S./Ph.D. in a quantitative field such as computer science, data science, AI, machine learning, or related disciplines. •A minimum of 8 years as a hands-on AI practitioner developing and deploying AI-driven software solutions, with 4+ years in AI production solutions. •Expertise in training, fine-tuning, and optimizing foundation models, including large-scale LLMs and VLMs. •Strong experience with generative AI techniques, including transformers, diffusion models, and self-supervised learning. •Deep knowledge of AI, deep learning, machine learning, and statistical modeling methods for both supervised and unsupervised learning. •Proficiency in AI frameworks such as PyTorch and TensorFlow, along with experience deploying models using NVIDIA Triton or similar inference platforms. •Experience deploying AI models into production, including handling live video feeds and real-time inferencing. •Strong problem-solving skills and ability to lead cross-functional teams in solving complex AI challenges. •Excellent communication skills, with the ability to present technical concepts effectively to diverse audiences.