Junior ML Engineer (Portugal Based Remote/Hybrid)

at  SWORD Health

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 post-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 best-in-class clinical results. Since breaking into the market less than two years ago, Sword has worked with insurers, health systems, and employers in the U.S., 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.

• Contribute to designing, building, evaluating, shipping, and improving Sword’s products through hands-on AI/ML development;
• Develop and maintain data processing pipelines for getting the data required to build and evaluate models;
• Share your knowledge and experience of how to build ML systems.