Software Engineer; Member Technical Staff

Member of the Technical Staff - Software Engineer

About Transfyr

Transfyr is building physical AI for science.

Why is it that a professional athlete has dramatically more information about every play they make than a scientist has about the cause of any experimental failure? At Transfyr, we are building the infrastructure to make real-world scientific work legible, transferable, and reproducible.

Modern science is capable of extraordinary outcomes, but much of the most important insights never become explicit: how experiments are actually executed, protocols drift, how experts make gametime decisions on the fly, why experiments fail on Tuesdays. This tacit knowledge is rarely captured, making it difficult to reliably reproduce results, much less hand off protocols to new team members or collaborators.

We believe our systematic failure to capture tacit knowledge is holding back the entire industry.

We’re building systems that operate directly in real laboratory environments to elucidate, capture, and interpret this missing information. Our platform records and analyzes multimodal data about how scientific work is performed and turns it into durable, operational knowledge. In doing so, we are also building the world’s largest commercial dataset on real-world scientific execution.

This foundation is critical not only for driving elite human performance today, but for enabling meaningful automation tomorrow. Physical AI systems cannot learn from outcomes alone; they require rich, grounded records of how work is actually done in the real world.

Want to learn more? You can read some of our writings here.

Software engineers at Transfyr design and build the core systems that make real-world science legible.

You will work on end-to-end software systems that ingest, organize, and serve multimodal data from complex laboratory workflows. This is much deeper than just a pretty UI, your software will touch physical environments, imperfect humans, ever-evolving protocols, and long-tail failure modes. The work demands strong engineering fundamentals, high agency, and comfort operating where requirements emerge from reality rather than specs.

We re building a team, and we have needs across levels:

• Hands-on builders early in their careers who are excited to build and ship real systems quickly
• Senior engineers who enjoy shaping system boundaries, abstractions, and long-term technical direction.

This role is in-person in Cambridge, MA (other locations may open in the future, feel free to reach out even if Boston is not currently an option for you).

• Build the Backbone: Develop and implement core software systems that enable reproducible, legible, and scalable science in real world laboratory environments.
• Tame the Data: Build data pipelines and services that ingest, transform, and organize multimodal data (e.g., events, metadata, media, sensor outputs) generated by scientific workflows and support both rapid experimentation and production use.
• Make It Robust: Develop reliable infrastructure that supports both rapid iteration and production-grade robustness.
• Structure Reality: Collaborate closely with AI and ML engineers, perception engineers, scientists, and operations teams to translate evolving real world needs into robust software abstractions.
• Own the End-to-End: Take cross-functional initiatives from concept to deployment, helping define system boundaries, milestones, and technical tradeoffs.
• Ship Tools People Trust: Develop internal and customer facing tools that make complex systems understandable and usable for scientists and operators.
• Enable What Comes Next: Evaluate and integrate external tools, open source software, and infrastructure components where they accelerate progress.

• High agency. You don’t wait for perfect specs, detailed tickets, or constant direction. You notice what needs to be done, anticipate downstream needs, and take ownership of pushing important work across the finish line.
• Biased toward action. You value momentum, can move quickly without being careless, and know when to trade elegance for progress.
• Successful in ambiguity. You can turn incomplete…