Engineering Manager, Embedded

Reposted 16 Days Ago
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London, Greater London, England
In-Office
171K-171K Annually
Senior level
Artificial Intelligence • Software • Semiconductor
The Role
Lead and manage the Embedded Systems Engineering team, defining strategies and overseeing project execution to connect optical hardware with real-world applications.
Summary Generated by Built In

As our Engineering Manager, Embedded Systems, you’ll lead the team building the embedded layer that makes this breakthrough possible.

The Role:

You will lead and scale Flux’s Embedded Engineering team, responsible for the core systems that connect our optical hardware to the real world - from post-silicon validation and baseboard management to thermal and analog control. You’ll define technical strategy, drive execution, and help build one of the most technically ambitious teams in the industry.

Key Responsibilities:

  • Lead and grow a high-performing embedded engineering team in a fast-paced, high-expectation environment.

  • Own delivery of complex, cross-functional projects across optics, hardware, and software that drive customer and business outcomes.

  • Shape the engineering strategy and architecture, aligning embedded systems development with Flux’s broader product roadmap and technical vision.

  • Build organisational capacity by hiring exceptional engineers, mentoring emerging leaders, and establishing scalable processes.

  • Drive quality and reliability across post-silicon validation, control systems, and firmware development.

  • Partner cross-functionally with optics, hardware, and software teams to bring the OTPU to market.

Skills & Experience:

In order to set you up for success as an Engineer Manager at Flux, we’re looking for the following skills and experience:

  • Have 5+ years of experience managing engineering teams of 5-10 in a high-performance, fast-paced environment. Experienced in hyper-scaling and managing managers preferred.

  • Proven experience leading post-silicon validation, baseboard management controllers, and thermal/analogue control systems in C/C++.

  • Strong track record of leading world-class teams and delivering customer and business outcomes.

  • Thrive in ambiguity and can adapt quickly to rapidly changing conditions.

  • Have experience closing competitive candidates for your team, and the ability to craft and convey compelling visions of the future

  • Have a strong coaching mindset and excel at guiding engineers to reach their peak potential.

Compensation & Benefits:

  • £171,000+ annual salary, depending on experience, skills, and location.

  • Competitive stock options, you’re not just part of the journey, you will own a piece of it.

  • Work from our HQ in King’s Cross, right in the middle of London’s buzzing AI scene.

  • Live within 45 minutes of the office? Perfect. Live within 20 minutes? We’ll add an extra location bonus to your salary.

  • We offer visa sponsorship and full relocation support (UK and abroad), through a dedicated third-party provider who are on hand to make your move to London as seamless as possible.

  • Full BUPA healthcare and dental cover, medical history disregarded.

  • High-spec tech for everyone - M4 Macs as standard, M4 Pros for Engineers.

  • Sony noise-cancelling headphones and ergonomic setups to keep you comfortable and focused.

  • Personal company card to spend on tools that help you do your job - like ChatGPT Pro or anything else that boosts your workflow.

  • Healthy, chef-cooked dinners in the office every night, with something for every diet and tastebud.

  • Monthly off-site team socials.

  • 25 days of paid holiday, plus all the UK bank holidays.

  • Access to our in-house 3D printer for personal or work projects.

  • Cycle2work scheme.

  • Need a caffeine fix? We’ve got you covered with a tab at our favourite local coffee shop.

  • We offer a pension plan and salary sacrifice options.

Top Skills

C
C++
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The Company
40 Employees
Year Founded: 2024

What We Do

Flux Computing designs and manufactures optical processors to train and run inference on large AI models.

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