Senior Applied AI Engineer, Life Science Markets

Job not on LinkedIn

🔥 5 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Vi

WebsiteLinkedInAll Job Openings

51 - 200 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Vi is a company that leverages artificial intelligence to help health organizations improve member health outcomes and financial returns. The company provides an AI SaaS platform that offers solutions for efficient acquisition, personalized engagement, and predictive retention throughout the member lifecycle. Vi focuses on maximizing acquisition, enrollment, engagement, retention, upsells, and health outcomes with superior ROI. Their platform is designed to lower the cost per acquisition, enhance member engagement and retention, and transform operations with their generative AI technology. Vi works with leading global health enterprises to drive results at scale while ensuring privacy and data security standards are met.

📋 Description

• Design, build, and deploy AI-powered applications, services, and data workflows • Work hands-on with engineers, data scientists, and domain experts • Own implementation from prototype through production • Design and implement systems combining ML models, LLMs, retrieval, and workflow automation for life sciences market questions • Make practical choices about model quality, reliability, latency, and cost • Build automated tests, evaluation datasets, and monitoring for AI outputs and application reliability • Maintain rigorous validation of predictive models, including point-in-time backtesting, baseline comparisons, and checks for leakage and coverage bias • Take prototypes into production and own APIs, integrations, deployment, observability, and incident resolution • Build reusable capabilities that scale across therapies, companies, and clients • Work directly with clients and domain experts to understand analytical workflows, explain findings, challenge assumptions, and turn feedback into product priorities

🎯 Requirements

• Track record of independently shipping applied AI applications or services, from initial prototype to production use • Practical experience integrating ML models and LLMs into software, including retrieval, tool use, structured outputs, and evaluation • Sound judgment about model limitations and when a simpler approach is sufficient • Ability to run working sessions with clients’ technical and non-technical stakeholders and identify impactful solutions • Strong software engineering fundamentals, including API design, testing, version control, and maintainable code • Experience deploying and operating AI systems, including CI/CD, model versioning, monitoring, and troubleshooting • Ability to work with large datasets in the cloud, ideally using AWS services such as S3, Glue, EMR, MWAA, and SageMaker • Sound judgment with incomplete or noisy data • Clear communication and ability to work independently within a cross-functional squad and with client stakeholders • Background in life sciences, pharmaceutical analytics, or capital markets helpful but not required

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