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Transfyr is building physical AI for science and the world's largest commercial dataset on real-world scientific execution. The company deploys sensors (vision, audio, environmental) in laboratory environments and provides a platform that records and analyzes multimodal data about how scientific work is performed.
As a Field Applications Engineer, you will be the bridge between Transfyr's AI technology and real-world laboratory environments. You own the physical realization of the platform at customer sites, from hardware procurement and assembly through field deployment and customer success.
Key responsibilities include:
• Hardware Procurement & Assembly: Source and physically assemble multi-sensor arrays, networking infrastructure, and edge compute kits, managing logistics for timely deployments.
• Robustness Testing: Design and execute stress tests on hardware configurations before field deployment to ensure reliable operation in varied laboratory conditions.
• Customer Field Deployment: Own end-to-end installation and setup at customer sites, overcoming site-specific infrastructure challenges to get sensors live and data flowing.
• Scientific Problem Solving: Partner with customer scientists to understand workflows and design bespoke sensor placements or solutions that make their experiments legible.
• Internal Synthesis & Growth: Translate field observations and customer feedback into structured requirements for Hardware, Software, Perception, and AI/ML teams.
• Customer Success: Own realized value post-deployment, triage and resolve first-line hardware/software issues, and surface quick-win opportunities by translating platform data into actionable insights.
You are high-agency, biased toward action, and successful in ambiguity. You move quickly without being careless, balance speed with correctness, and communicate clearly with colleagues across technical and non-technical backgrounds. You have experience managing physical hardware and networking installations in complex environments, ideally in scientific laboratories. You understand customer engineering, sensor integration, networking basics, and edge system maintenance. Experience with infrastructure-as-code and edge-to-cloud data transfers is valuable. A deep curiosity for science and familiarity with process development are important. Startup experience and passion for AI are bonuses.
The role is in-person in Cambridge, MA, with significant travel nationwide (up to 25%). The company is well-funded and led by founders from Ginkgo Bioworks, Bain Capital, DARPA, and ARPA-H.
