Inspired by the sigmoid function, a foundational concept in machine learning, SigmaMD is revolutionizing healthcare management. We're at the forefront of developing AI-powered applications that foster stronger physician-patient relationships and enable patients to take a proactive role in their healthcare. We're looking for an experienced and passionate Senior AI Engineer to help us harness technology to positively impact millions of lives. You must be a proactive self-starter who can lead projects independently, take initiative, and drive results while working independently with guidance. Responsibilities: Lead the development of AI models to assist and improve the clinician and patient workflows. Utilize existing foundational models to develop innovative algorithms, with a focus on embeddings and their applications. Follow a complete cycle for AI implementation: problem understanding, data collection, data cleaning, model training, model evaluation, model deployment, and performance monitoring. Collaborate with a cross-functional team, including engineers, product, and clinicians, to ensure the developed models align with the healthcare needs. Stay abreast of the latest advancements in AI and Machine Learning, specifically in the healthcare domain, including continually reading up on relevant research papers and integrating newfound knowledge into our product development. Required Skills: Proven experience in developing and implementing successful AI strategies for technology products. Strong understanding and hands-on experience with foundational AI models such as GPT-4, Med-PaLM 2, or similar. Experience in designing and implementing AI models for real-world applications. Strong ability to collaborate with multi-disciplinary teams of business analysts, data scientists, subject matter experts, and developers. Excellent communicator and problem solver. Master's degree or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. Good to Have: Experience in a startup or healthcare technology environment. Experience with data-sensitive products. Understanding of the unique nature and constraints of medical data. For more information about our work, visit our website at Feel free to contact us with any questions, and we'll do our best to reply back promptly.