Sr. Software Engineer for Edge AI Applications in Ely

UBIETY Technologies Ltd. requires a senior software engineer to develop the software stack for precision Edge-AI measurement instruments serving energy-transition, industrial and healthcare markets. Each instrument couples an analogue front end with a modern SoC-FPGA platform combining programmable logic (PL) with an embedded processing system (PS). The role works alongside an FPGA specialist, who owns the PL for deterministic timing, acquisition and high-rate data movement, and an algorithms engineer, who develops the measurement algorithms in MATLAB and Python.

The software engineer owns the PS side of the PS–PL boundary: register maps, DMA buffers, interrupts, device tree, embedded Linux services for control, processing, diagnostics, industrial communication and user interaction, and the backend processing and user-facing interfaces. A central task is to translate the MATLAB/Python reference algorithms onto the PS — and, with the FPGA specialist, onto the PL. The three roles operate as a single team, and broader cross-disciplinary collaboration is expected and valued.

Primary ownership

• Embedded Linux: Board software, Linux application services, boot/runtime configuration, logging, watchdogs and deployment.
• PS–PL integration: AXI-Lite control, AXI DMA integration, DDR buffer management, interrupt handling, packet formats, deserialisation boundaries and PL bring-up tools.
• Backend processing: Acquisition orchestration, waveform capture, diagnostic extraction, path health checks, flow-computation support and data persistence.
• Industrial interfaces: Ethernet services, Modbus TCP register map, process-variable publishing, alarm/status words and configuration access.
• User interface: Browser-based or desktop UI for commissioning, operation, calibration, diagnostics, event logs and service access.
• Measurement integrity: Audit trail, protected calibration parameters, version traceability, configuration CRC, role-based access and controlled update/rollback.

Essential skills

• Embedded Linux: Yocto or PetaLinux, U-Boot, kernel/device-tree awareness, systemd, cross-compilation, network configuration and field update strategy.
• C/C++ backend: Modern C++ and C for low-level interfaces, multithreading, bounded queues, binary protocol handling, error handling, performance profiling and CMake/Make.
• PS–PL interface: AXI-Lite, AXI-Stream, AXI DMA/CDMA, memory-mapped I/O, UIO/VFIO or kernel drivers, interrupts, cache coherency, contiguous buffers, serial-link bring-up and deserialised packet validation.
• Signal processing & algorithm porting: ADC sample streams, filtering, FFT, cross-correlation, parameter estimation, interpolation, SNR, clipping, gain and channel diagnostics; translating MATLAB/Python reference algorithms into efficient, validated embedded C/C++.
• Edge AI deployment: On-device inference of trained models on SoC-FPGA targets using vendor toolchains (e.g. Vitis AI/DPU) or equivalent runtimes: ONNX import, model quantisation and optimisation, fixed-point/integer pipelines and PS–PL partitioning of the inference workload.
• Communications: Modbus TCP, TCP/IP sockets, REST/WebSocket APIs, register scaling, engineering units, endian handling and alarm/status design.
• UI implementation: TypeScript with React/Vue/Svelte or equivalent, real-time charts, configuration screens, service pages, role-based access and waveform snapshots.
• Quality discipline: Git, issue tracking, test automation, reproducible builds, logging, fault injection, diagnostics and release documentation.
• Data & persistence: SQLite or time-series stores on embedded targets, ring buffers, log rotation, long-term onboard historical data retention and export formats (CSV/JSON/binary) for analysis tools.
• Real-time & performance: Linux real-time tuning (PREEMPT_RT awareness), CPU affinity and thread priorities, latency measurement, zero-copy I/O and memory budgeting on resource-constrained embedded targets.
• Build tooling & CI: Containerised cross-build environments (e.g. Docker), CI pipelines building and testing for embedded targets, artefact versioning, SBOM awareness and reproducible release packaging.

Desirable background

• SoC-FPGA platforms (e.g. AMD Zynq-class), industrial instrumentation, test-and-measurement systems.
• Medical or industrial imaging and reconstruction pipelines (e.g. ultrasound, MRI, CT).
• Edge AI/ML: Vitis AI tooling, model quantisation/pruning, TVM/TensorRT or equivalent, and hardware-aware optimisation of ML inference. Interest or experience in SciML such as PINNs/PIML as well as generic PyTorch/TensorFlow is a distinct advantage but not mandatory.
• Legal-metrology or other regulated-measurement environments: auditability, calibration locking, tamper evidence and secure device service access.
• OPC UA, MQTT, TLS/certificates, signed updates, A/B root filesystem deployment and factory-test automation.
• Python for hardware-in-the-loop test rigs, automated regression testing and measurement data analysis alongside MATLAB.

Employee Benefits

• Modern, fully refurbished Ely offices; free parking; walking distance to Ely rail station.
• 25 days annual leave + Bank Holidays, rising to 30 days with service.
• Auto-enrolment workplace pension (optional, with opt-out under UK rules).
• Healthcare provided automatically, non-contributory.
• 9am-5pm with one-hour lunch; role-based flexible / remote working day.
• Cycle to Work scheme; supported team activities (e.g. staff rowing on the River Great Ouse).
• Performance-based share options after 3 years' employment.

For more information about UBIETY Technologies Ltd., visit: www.ubiety-technologies.com.