Senior GenAI Research Engineer (AI Agent), Digital Health
Samsung Research America665 Clyde Avenue, Mountain View, CA, USAPosted 12 March 2026
Job Description
Lab Summary:
We are an interdisciplinary team with an aim to empower providers, consumers, and clinical researchers. We develop GenAI/LLM-based health applications for engaging customer experience, create prognostic biomarkers by applying clinically explainable AI on advanced sensing technology, explore use cases by co-innovating with our partners, and design services through pilots that eventually turn into groundbreaking commercial, consumer-grade products that are used every day. Our work has been internationally recognized with 100+ peer-reviewed publications.
Position Summary:
Samsung Research America Digital Health Team is looking for an outstanding Senior-level ML Research Engineer with solid Generative AI/Large Language Model technology background and extensive industry experience in building, scaling and optimizing ML pipelines. You must have a strong track-record of success in commercializing GenAI/LLM products. You will play a key role in delivering innovation in digital health domain, create technologies, deploy and validate novel technologies, and transfer code to production. You will also author scientific publications in top-tier computing venues. This team is the right fit for you if you love working with the latest technologies in LLMs, MLOps and ML more broadly.
You will be a core part of a passionate team charged with developing, incubating, and launching a portfolio of digital health product concepts that will disrupt the healthcare paradigm. By leveraging smart phones, wearables, embedded devices and the IoT in the health/wellness domain, your work will significantly benefit real-world patients, seniors, physicians and care givers. Samsung’s unique advantage in the consumer electronics market and growing focus on digital health will provide you with exciting technical challenges and a rewarding career experience.
Position Responsibilities:
Lead the development of our next-generation autonomous agent ecosystem. In this role, you will bridge the gap between state-of-the-art ML research and production-grade consumer applications, specifically focusing on multi-agent orchestration and standardized communication protocols. You will be responsible for building resilient, interoperable agents that solve complex, multi-step tasks at scale while adhering to emerging industry standards like A2A and MCP.
This role requires a unique blend of deep theoretical knowledge in LLMs and a proven track record of shipping production-grade AI features to millions of users.
Agentic System Architecture: Design and deploy sophisticated multi-agent systems capable of long-horizon reasoning, planning, and autonomous task completion.
Protocol Standard Adoption: Implement and optimize agentic workflows using the Model Context Protocol (MCP) for seamless tool and data integration.
Interoperability Leadership: Architect cross-platform collaboration using the Agent-to-Agent (A2A) protocol to enable secure communication and task delegation between independent agents.
End-to-End Product Delivery: Translate research breakthroughs into high-impact consumer features, managing the full lifecycle from prototyping to large-scale production deployment.
Advanced Evaluation Safety: Develop robust evaluation frameworks—including LLM-as-a-Judge and scenario-based testing—to ensure agent reliability, safety, and alignment.
Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap.
Required Skills:
MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, or equivalent combination of education, training, and experience
5+ years of experience in ML, with a strong track record of shipping consumer-facing AI products at scale
Experience building and deploying scalable GenAI/LLM applications, with tools such as VertexAI, HuggingFace, Langchain and OpenAI
GenAI Expertise: Deep understanding of transformer architectures, LLM fine-t ... (truncated, view full listing at source)
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