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Full-Stack PHP Developer

Provider Success Manager

As a Provider Success Manager at Regard, you will own the education process and provider relationship throughout the contract period for assigned client organizations. You will collaborate closely with the Customer Experience team and will be responsible for scheduling education, shadow, and debrief sessions; building relationships with individual clinicians; identifying and escalating barriers to adoption; and recommending opportunities to improve onboarding, clinician communication, and user feedback processes. In addition to client-facing responsibilities, this role actively contributes to improving how the Provider Success team operates by identifying inefficiencies, piloting new approaches, and owning or supporting internal process improvement initiatives that scale education quality and clinician adoption. This role will report to the Director of Provider Success and will work closely with members of the Customer Experience, Sales, Marketing, Product, and Engineering teams to Ple

Machine Learning Engineer

About Radformation Radformation is transforming the way cancer clinics deliver care. Our innovative software automates and standardizes radiation oncology workflows, enabling clinicians to plan and deliver treatments faster, safer, and more consistently, so patients everywhere can receive the same high-quality care. Our software focuses on three key areas: Time savings through automation. Error reduction through automated systems. Increased quality care through advanced algorithms and workflows. We are a fully remote, mission-driven team united by a shared goal: to reduce cancer’s global impact and help save more of the 10 million lives it claims each year. Every line of code, every product release, and every conversation with our customers brings us closer to ensuring no patient’s treatment quality depends on where they live. Why This Role Matters In this role you will help advance Radformation’s AI-driven radiotherapy products by building and improving machine learning models