Top Remote Senior Level Python Jobs in Boise, ID

The Software Engineer will lead a team in expanding REPAY's payment processing platform, provide mentorship, collaborate on technical requirements, and ensure adherence to coding standards while participating in the full software development lifecycle.

As a Senior or Staff Software Engineer on the Data Product team, you will design and build scalable data services that analyze blockchain transaction activity. You will collaborate with data scientists and engineers to enhance TRM's products through efficient data models and architectures. Your role involves hands-on experience in API development, distributed systems, and utilizing various data processing technologies.

The Solutions Engineer II will engage in pre and post-sales technical interactions, perform radar demonstrations, oversee installation and integration, manage customer relationships, and provide technical support. This role may also involve travel up to 50%.

As a Principal Software Engineer at Nava, you will lead FHIR-based software services, collaborating with clients, developing strategic roadmaps, and ensuring adherence to HL7 standards while enhancing user experiences through software engineering tasks and documentation.

The Senior Applied Scientist will leverage generative AI and machine learning to tackle complex business challenges at Wellth. Responsibilities include researching current operations, building prototypes for optimizing member experience, deploying generative AI solutions, and collaborating with product and engineering teams. The role aims to significantly scale Wellth's health rewards program while improving health outcomes for many.

The Full-Stack Engineer will develop and maintain front-end and back-end solutions to support satellite owner-operators. They will work with cross-functional teams, participate in Agile processes, and build data platforms and APIs while mentoring fellow engineers and delivering high-quality code.

The Data Science & AI Platform Engineer will build and maintain a secure, cloud-hosted production laboratory for data science teams to create analytics and deploy AI/ML models. Responsibilities include developing data readiness pipelines, managing cloud services like AWS, and integrating modern tools for data analysis and machine learning.