.Senior Ml Engineer (Portugal Based Remote/Hybrid) PortoJob Description:Who we are: Each year, 2 billion people across the world are limited by physical pain. By helping people live without pain, they are free to do the things they love most with the people they love—and never miss a moment. This is what we do. We create and design new technologies to solve one of the biggest problems in healthcare: taking care of our Physical Health. Sword Health is the world's fastest growing digital musculoskeletal (MSK) care provider on a bold mission to free two billion people from acute, chronic, and surgical physical pain. Our customers include some of the most progressive Fortune 100 and 500 companies, as well as over 160+ other established businesses across the world. The Sword program allows members to complete a personalized physical therapy program from the comfort of home, with continued support and supervision from one of our talented SWORD specialists. Sword's personalized care is more effective than traditional standards of care and has proven to deliver class clinical results. Since breaking into the market less than two years ago, Sword has worked with insurers, health systems, and employers in Canada, Europe, and Australia to make high quality musculoskeletal care accessible to everyone. This is an opportunity to join Sword during a time of hyper growth and expansion. After our recent $2bn valuation, we're excited to continue accelerating our impact by scaling with high caliber people with passion, commitment, and energy to create and deliver technologies, services, and products that drive human progress forward. We welcome you to join our mission, to make a difference on a grand scale and play a pivotal role with a global team at Sword– working alongside great people pioneering novel products and cutting edge technologies.The AI team: The main goal of the AI Team is to leverage AI and ML to provide quality clinical care at unprecedented levels of personalization and scale. In this regard, in close collaboration with the clinical team, we develop ML-powered features that identify the best course of action for each patient at any given moment or circumstance whilst employing a holistic perspective but also contemplating any relevant nuance. We also work on ensuring the overall experience is as close as possible to a 1:1 session with a Physical Therapist and thus play a crucial role in enabling the AI Care provided by Sword. Some examples of the work we did so far include a decision support system for managing clinical prescriptions, a classification system that identifies people in need of assistance, and a system that enhances the Physical Therapist context when communicating with the patient. To achieve this, we work with tabular and text data using a combination of classical methods and more recent models (such as LLMs)
