Staff GenAI Research Engineer, Digital Health

Samsung Research America • Mountain View, CA

4d • Onsite

About The Position

Samsung Research America Digital Health Team is looking for an outstanding Staff-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 industrial settings 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 the mature outcomes to production and scientific publications in top-tier computing venues. We expect candidates who have solid technical skills and project experiences in areas of generative AI and Large Language Models. This team is the right fit for you if you love working with the latest trend and 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.

Requirements

• MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, r equivalent combination of education, training, and experience
• 8+ 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-tuning, and modern generative AI methodologies
• Prompting Frameworks: Hands-on experience with DSPy (Declarative Self-improving Language Programs) or similar programmatic optimization frameworks
• Technical Stack: Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
• Evaluation Expertise: Demonstrated experience building scalable, data-driven frameworks to measure LLM performance, safety, and robustness in real-world scenarios
• Strong interpersonal and collaboration skills, ability to present complex information in an understandable and compelling manner, and comfortable working with multi-disciplinary teams

Nice To Haves

• Experience in NLP and Conversational AI
• Experience in LLM validation, reliability, toxicity/harmfulness avoidance
• Strong mathematics background, especially statistics
• Turn the analyzed data into actionable insight and/or understandable visualization
• Product development and prototyping experience in order to implement and validate solutions
• Have working knowledge of the healthcare industry and experience curating and analyzing healthcare and wellness data
• Experience in collaborating on software implementations of algorithms and computing models with client and cloud engineers
• Experience operating under HIPAA/CCPA/GDPR is a plus
• Experience with agentic workflows, multi-step reasoning, and tool-use integration
• Contributions to open-source GenAI projects or publications at top-tier AI conferences (NeurIPS, ICML, ICLR)

Responsibilities

• Bridge the gap between cutting-edge machine learning research and the delivery of high-impact consumer applications.
• You will be responsible for designing and optimizing large-scale generative systems, with a specialized focus on programmatic prompt optimization and scalable evaluation frameworks.
• Prompt Programming & Automation: Architect and implement automated prompt tuning pipelines using frameworks like DSPy to replace manual "prompt engineering" with structured, optimizable code.
• Scalable Evaluation Frameworks: Design and build robust, automated evaluation infrastructure for GenAI applications, including LLM-as-a-Judge autorater systems, regression tracking, and golden test sets at scale.
• Product Implementation: Collaborate with product and UX teams to translate research breakthroughs into seamless, production-ready consumer features.
• Optimization & Scaling: Develop and maintain high-efficiency inference pipelines and ML pipelines for rapid iteration and production deployment.
• Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level