Founding Embedded & Edge AI Engineer

Inframesh; Greater London; Hybrid; GBP 75,000 - 110,000; Full time

Job summary

Inframesh is building the intelligence layer for buildings. We seek an engineer to own the software path from raw electrical signals to the product interface, working across embedded Linux, data acquisition, edge inference, APIs and the first production dashboard.

This hands-on role spans hardware integration, system-level debugging and delivering end-to-end software for a real-time energy monitoring product. London hybrid work is expected with frequent hardware collaboration.

Qualifications

• Strong Python and Linux experience.
• Experience deploying software onto devices outside your development environment.
• Experience with time-series, sensor or signal-processing data.
• Practical experience deploying or adapting ML models and inference pipelines.
• Ability to build/maintain a React or Next.js interface from designs.
• Good ownership mentality across cross-functional boundaries.

Responsibilities

• Build and harden the software running on our embedded Linux devices.
• Own the data path from sampling through buffering, timestamping, processing and labelled records.
• Integrate and optimise our ML inference pipeline on target hardware.
• Tune inference for latency, memory usage, stability and long unattended operation.
• Build APIs and event streams for the dashboard and external partners.
• Own device provisioning, connectivity recovery, logging, remote diagnostics and OTA updates.
• Take Next.js/React app and Figma designs to production deployment.
• Build live product views for power data, appliance activity, consumption history and events.
• Collaborate with firmware and hardware engineers during integration and field deployment.

Skills

Python

Linux

Time-series data

ML model deployment

React/Next.js

Hardware debugging

Ownership mindset

Job description

Inframesh is building the intelligence layer for buildings.

Our system measures the electrical fingerprint of a building in real time using our own sensing hardware and on-device AI, turning raw electrical signals into an understanding of how a building is operating.

Our first hardware is built and under test, with partner deployments beginning shortly. We are now looking for an engineer who can take ownership of the software path from raw electrical signals through to the product interface.

This is a broad, hands-on role at an early-stage hardware and AI company. You will work across embedded Linux, data acquisition, edge inference, APIs, device management and the first production version of our customer dashboard.

What you will do

• Build and harden the software running on our embedded Linux devices
• Own the data path from sampling through buffering, timestamping, processing and labelled records
• Integrate and optimise our existing machine-learning inference pipeline on the target hardware
• Tune inference for latency, memory usage, stability and long unattended operation
• Build the APIs and event streams used by our dashboard and external partners
• Own device provisioning, connectivity recovery, logging, remote diagnostics and over-the-air updates
• Take our existing Next.js/React application and Figma designs through to a production-ready deployment
• Build live product views for power data, appliance activity, consumption history and detected events
• Work closely with our firmware and hardware engineers through system integration and field deployment

What we are looking for

• Strong Python and Linux experience
• Comfortable working close to hardware and debugging real systems
• Experience deploying software onto devices operating outside your own development environment
• Experience with time-series, sensor or signal-processing data
• Practical experience deploying or adapting machine-learning models
• Comfortable with model optimisation, quantisation, evaluation and inference pipelines
• Able to build and maintain a React or Next.js interface from an existing design
• Strong ownership mentality and comfortable working across boundaries rather than inside a narrowly defined software role

Experience with robotics, IoT, industrial systems, embedded AI, energy monitoring or edge computing would be especially relevant.

Knowledge of electrical measurement, harmonics, power systems or high-frequency signal processing is useful but not required.

About the AI

We already have an existing machine-learning pipeline and training data.

Core model development is supported by our technical advisors, including Professor Ahmed Zoha, an expert in AI for energy systems.

You will own how those models operate in the real product: deployment, optimisation, evaluation, data quality, feedback loops and reliability in the field.

About the role

You would be joining at an early stage, with significant ownership over the architecture, implementation and technical direction of the product.

This is best suited to someone who enjoys building complete systems rather than owning only one layer of the stack.

Location:

London, hybrid — expected to work in person several days a week, particularly for hardware integration, testing and deployments