Applied ML Engineer, Care Experience

Job not on LinkedIn

🔥 11 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 25%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Just posted.
• Jobs at this company usually fill in 60 days.
• 102 open roles for a team of 16.
• No salary listed.

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Bask Health

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

💰 Pre Seed Round on 2022-05

Healthcare • Consulting • Logistics

Bask Health is a robust platform providing a comprehensive suite of customizable telehealth solutions. It offers tools such as a questionnaire builder, patient portals, and pharmacy fulfillment services, all secured with strong encryption and HIPAA-compliance. Bask Health seamlessly integrates telehealth and e-commerce, enabling streamlined patient care from consultation to delivery. The platform supports entrepreneurs, doctors, and developers by offering scalable no-code solutions that enhance user experience and business growth. With its nationwide pharmacy network, Bask Health empowers businesses to efficiently manage prescriptions, patient data, and order fulfillment across the entire digital health landscape.

📋 Description

• Build and maintain machine learning and AI-powered capabilities that support ongoing patient care experiences. • Develop intelligent systems for approved patient support and care coordination workflows. • Implement machine learning models that classify and organize patient-related administrative requests. • Build AI-assisted tools that help authorized teams understand and manage incoming communications. • Develop routing and prioritization systems for operational tasks and support requests. • Implement intelligent workflow assistance for follow-ups, status updates, and administrative coordination. • Build backend services and APIs that connect ML capabilities to existing platform applications. • Integrate large language models into approved care-related operational workflows. • Develop structured output pipelines that convert model responses into validated application data. • Build information retrieval capabilities that surface relevant approved workflow information. • Implement AI-assisted summaries for authorized care and operations teams. • Develop systems that help identify incomplete administrative workflows or delayed operational handoffs. • Evaluate opportunities to apply predictive modeling to approved care experience use cases. • Design feature engineering and data processing workflows for machine learning applications. • Build automated tests for model outputs, APIs, and application behavior. • Evaluate models for accuracy, relevance, consistency, and operational usefulness. • Investigate incorrect classifications, unreliable responses, and unexpected model behavior. • Improve model configurations, prompts, and application logic based on evaluation results. • Implement human review and confirmation steps for sensitive workflows. • Ensure ML-powered features respect user permissions and approved data access. • Collaborate with product and operational stakeholders to define measurable success criteria. • Monitor production model behavior, application errors, and workflow performance. • Optimize inference latency, reliability, and operational costs. • Work with backend engineers to integrate ML services into production infrastructure. • Support controlled deployment and testing of new intelligent care experience features. • Document model assumptions, known limitations, and workflow safeguards. • Participate in code reviews, technical planning, and architecture discussions. • Own assigned applied ML features from development through deployment and ongoing improvement.

🎯 Requirements

• 3+ years of professional experience in machine learning engineering, software engineering, applied AI, or a closely related technical field. • Experience developing and deploying production software or machine learning applications. • Strong programming skills in Python, TypeScript, or comparable languages. • Familiarity with machine learning models and practical model evaluation techniques. • Experience building AI-powered applications or integrating machine learning capabilities into software products. • Understanding of large language models and modern generative AI development patterns. • Experience developing backend services and application APIs. • Familiarity with model APIs, structured outputs, and application integrations. • Experience working with relational databases and structured application data. • Understanding of classification, prediction, or other applied machine learning methods. • Familiarity with data processing and feature preparation workflows. • Experience writing automated tests for production software. • Ability to evaluate model outputs and identify accuracy or reliability problems. • Understanding of authentication, authorization, and secure application design. • Familiarity with asynchronous processing and workflow automation. • Experience with logging, monitoring, and production troubleshooting. • Understanding of model limitations and common AI failure modes. • Familiarity with cloud-based application deployment. • Ability to translate operational requirements into technical solutions. • Understanding of responsible data handling and privacy-conscious development. • Experience using Git and collaborative engineering workflows. • Strong analytical and problem-solving skills. • Ability to communicate effectively with technical and nontechnical stakeholders. • Strong attention to detail and software quality. • Ability to independently own assigned engineering projects.

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