Senior Software Engineer, Edge Platform

For a century, the answer to “what’s in the pipe right now” was a grab sample to a lab with results back hours later. We answer it every second.

Laminar is building human-centric self-driving factories: the ones made of stainless steel pipes and reactors, that make what the world eats, uses, and wears. Proprietary inline sensors read the chemistry in the pipe. Foundation models grounded in physics and chemistry reason about how close the process is to its target. Process control software acts on the answer through the plant’s automation system in real time. Laminar Insights shows what happened, why, and what it saved.

A Laminar line uses about 20% less water and 20% fewer chemicals and runs 15% faster, with quality protected. Productivity and sustainability improve together. We run across six continents at manufacturers like Coca-Cola, Unilever, and AB InBev, backed by tier-1 investors in Physical AI.

We’re a polymathic team of 50 in Somerville: hardware and software engineers, chemists, AI researchers, factory operators, and go-to-market wizards under one roof. Nobody here is waiting to be asked what to do. You’ll see the problem, propose the fix, and own the outcome. We believe in autonomy, ownership, and demanding excellence, and we hold each other to it. If that’s how you want to spend your time, come build the self-driving factory with us.

• 4+ years of experience building production systems software, with meaningful work on Linux systems, infrastructure, or distributed systems.

• Track record of owning the design, implementation, and success of significant components within a larger system.

• Comfortable defining technical direction, taking ownership, and delivering in a fast-paced product iteration cycle.

• Deep Linux experience, covering administration, networking, filesystems, troubleshooting, and performance analysis.

• Experience shipping software into environments you don’t control: into on-prem, edge, embedded, robotics, or similar.

• Practical experience with bare-metal infrastructure, hypervisors, virtual machines, and containers.

• Strong experience in languages such as Rust, Python, C/C++, or Go, with experience building automation and system tooling.

• Familiarity with deploying ML models and LLMs on edge hardware, including inference runtimes and resource constraints.

• Experience with deployment automation, monitoring, system recovery, and secure software updates.

• Bachelor’s or higher degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field, or equivalent practical experience.

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