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Transfyr is building physical AI systems that capture and digitize real scientific work, turning experimental execution into high-fidelity, machine-readable records. The company addresses a critical gap in science: the loss of tacit knowledge, decision-making, and process variability data that disappears when experiments end or scientists leave. This missing record hampers automation, training, tech transfer, and the development of useful AI/robotics for lab work.
As a Forward Deployed Engineer, you will embed with scientists and research partners to transform messy scientific data into actionable insights. This is a hybrid technical and field role—not purely software-based. You'll spend time in active lab environments collaborating with Field Application Engineers, combining protocol mapping, expert interviews, coding, multimodal data analysis, product workflow testing, and troubleshooting of deployments, hardware, and networking issues.
Key responsibilities include: learning real scientific workflows by embedding with researchers; converting observations, sensor data, and experimental outcomes into structured representations; designing minimal viable solutions before overbuilding; prototyping code and data analysis in the field; supporting protocol transfer across sites and teams; translating field insights into product requirements for software, perception, AI/ML, and hardware teams; owning deployment outcomes (not just installation); building reusable FDE methods and tools; and laying groundwork for future automation and troubleshooting agents.
You'll need wet-lab fluency, enough engineering skill to prototype quickly, strong product judgment, and a bias toward learning directly from users. The role demands high agency, comfort with ambiguity, customer obsession, and resourcefulness. You'll work in-person in Cambridge with regular travel to customer and partner sites (up to 20%). Transfyr is backed by a $25M seed round, collaborates with leading frontier AI labs, and is advised by Stanford researchers, Nobel laureates, and former OpenAI/Merck executives.
