Embedded Software Engineer

Salience Labs; Abingdon; On-site; GBP 52,000 - 72,000; Full time

Job summary

Salience Labs is seeking an Embedded Engineer to join our Software team in Abingdon. You’ll work on embedded systems at the heart of our technology, collaborating with hardware and system test teams to bring complex products to life.

This hands-on role emphasizes quick impact, code quality in C/C++, and a broad engineering mindset across software, hardware, and validation as we scale.

Qualifications

• 3+ years of embedded C/C++ experience.
• Ability to contribute to an existing codebase with minimal ramp-up.
• Strong analytical and debugging skills.

Responsibilities

• Contribute to the embedded software codebase, primarily in C and C++.
• Support product development, production testing, and customer-facing technical activities.
• Collaborate with hardware and system test teams to debug and optimise system performance.
• Take ownership of software tasks and deliver them to a high standard.
• Build a working understanding of the full product stack, beyond individual components.
• Help remove bottlenecks in the software team as we move towards wider product deployment.
• Work across engineering functions to ensure alignment between software, hardware, and system validation.
• Quickly get up to speed with development tools, environment, and product architecture.
• Support broader engineering needs, including manufacturing readiness and external demonstrations where required.

Job description

Job Overview:

We’re hiring an Embedded Engineer to join our Software team at a critical point in our growth. This role is essential to maintaining momentum across product development, production readiness, and customer delivery.

You’ll work on embedded systems that sit at the heart of our technology, collaborating closely with hardware and system test teams to bring complex products into the real world. While embedded software is central, this role suits someone with a broader engineering mindset, strong problem-solving instincts, and a genuine curiosity for how systems work end to end.

This is a hands‑on position where you’ll be expected to get up to speed quickly, contribute meaningfully from early on, and help reduce delivery bottlenecks as we scale.

What you’ll be doing:

• Contribute to the embedded software codebase, primarily in C and C++
• Support product development, production testing, and customer‑facing technical activities
• Collaborate closely with hardware and system test teams to debug and optimise system performance
• Take ownership of software tasks and deliver them to a high standard
• Build a working understanding of the full product stack, beyond individual components
• Help remove bottlenecks in the software team as we move towards wider product deployment
• Work across engineering functions to ensure alignment between software, hardware, and system validation
• Quickly get up to speed with development tools, environment, and product architecture
• Support broader engineering needs, including manufacturing readiness and external demonstrations where required

What we're looking for:

• Strong experience in embedded software development, ideally 3+ years using C or C++
• Proven ability to contribute to an existing codebase with minimal ramp‑up time
• Solid analytical and problem‑solving capability, with a structured approach to debugging
• Experience working in cross‑functional engineering teams, particularly alongside hardware
• A pragmatic, delivery‑focused mindset with good judgement on speed versus quality trade‑offs
• Clear communication skills, especially when working across technical disciplines
• A generalist engineering attitude, with curiosity beyond a narrow specialism

Even better if you:

• Have experience with non‑embedded software, such as Python or JavaScript
• Have worked with microcontrollers such as STM32 or Xilinx platforms
• Understand transport protocols such as I2C, SPI, PCIe, Ethernet, or AXI
• Can read and interpret hardware schematics
• Have some familiarity with networking or IT infrastructure
• Have exposure to machine learning concepts
• Have experience in early‑stage or deep‑tech environments