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Salary: USD 198,720 - 260,820 / annual
Oscar Health is seeking a Staff Applied AI Engineer to join its AI team and build transformative AI-powered products that redefine the healthcare experience. As a Staff-level engineer, you will take end-to-end ownership of high-impact projects—conceiving, prototyping, and deploying generative AI solutions that solve real-world problems across the healthcare ecosystem.
You'll work alongside a world-class team of engineers and data scientists, rapidly iterating on ideas and shipping production-ready applications that drive measurable business and user outcomes. Your responsibilities include leading the design, development, and deployment of AI-driven products and features from zero-to-one prototypes to robust production systems. You'll collaborate cross-functionally with product, design, and business teams to deeply understand user needs and deliver solutions that move key metrics.
You'll rapidly experiment with new models, techniques, and tools including LLMs, RAG, and agentic workflows, iterating based on data and user feedback. You'll build and scale full-stack applications and intelligent agents that automate complex healthcare workflows and deliver seamless user experiences. You'll stay on the cutting edge of the AI ecosystem, evaluating and integrating emerging technologies to keep Oscar at the forefront of healthcare innovation, and contribute to Oscar's AI strategy and technical vision.
The role requires 7+ years of professional experience in software engineering, data science, or a related field, with a track record of impactful accomplishments. You need 5+ years of experience as a leader of cross-pod or cross-company deliverables, leading technical contributions, and leading technical teams including mentoring and training junior engineers. Strong Python programming skills, experience solving complex ambiguous problems, designing and analyzing experiments, and prototyping full-stack applications are essential. Healthcare industry experience, familiarity with claims or clinical data, NLP/neural networks/transformers experience, and knowledge of containerization and deployment tools are bonuses.
