Senior Optical Engineer

Bunhill
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Lead Data Scientist - Customer Development

Data science programme lead

Data science programme lead

Senior Machine Learning Research Engineer

Senior Machine Learning Engineer

Senior Optical Engineer | London | Hybrid | £60k-£100K | Lucrative Stock Options

Are you an experienced Optical Engineer with experimental experience with Optical Systems? Are you looking to work on cutting edge products in AI and Machine Learning?

Then this might just be the role for you!

We are working with a disruptive London based Computer Networking company who are working on the cutting edge of AI and Machine learning technology with applications for increased productivity in Data Centre’s and HPCs.

They are looking for a Senior Optical Engineer to join them in their mission to revolutionise AI systems whilst reducing energy consumption and stiving for a sustainable future.

Key responsibilities:

Work within the optical network integration team with close collaboration with other teams.
Building optical testbeds and implement automated measurement methodologies for identification of System performance capabilities.
Modelling and characterisation of electrical and optical components and end-to-end systems.
Assessment of optical transmission and network performance for short-reach AI Networked Systems.Required experience:

Hands-on optical communication systems development and testing experience.
Experience with Optical Transmissions & Transceivers.
Experience with PAM4 & Passive Optical Networks.
High-baud-rate experience within optical communication systems.
Strong DSP and end-to-end optimisation experience.
End-to-end systems modelling experience, including RF and optical.
Strong Python skills for Test automation and scripting.
PhD degree in optical communications, physics, or other relevant fields or experience within the industry;What’s in it for you?

Up to £100k DOE
Lucrative stock options.
25 days holiday + bank holidays.
Hybrid working.
Relocation assistance.
Visa sponsorship provided

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.