National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Lab Technician (Optical Communication Networks)

Farringdon
1 week ago
Create job alert

Lab Technician (Optical Communication Networks) | London | Hybrid | Up to £50k | Lucrative Stock Options

Are you an experienced Lab Technician with a passion for electronics, optics/photonics, networks, systems and software? 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 Lab Technician to coordinate all aspects of lab operations on Optical Products to join them in their mission to revolutionise AI systems whilst reducing energy consumption and stiving for a sustainable future.

You will be expected to work on optical systems, networks and AI testbeds coordinating all aspects of lab operations from test and measurement equipment control and automation, procurement, optical and RF testbed configuration, and electronic design.

Candidates do not necessarily need experience in all these areas but genuine interest and passion for working on the cutting edge of communication networks and systems is a must.
 
Responsibilities

Overall management of lab facility.
Oversee Health and safety procedures.
Oversee control and automation of RF & optical test and measurement equipment.
Oversee and assist in setting up optical communication network testbeds.
Design of electronic circuits and PCBs.
Organise PAT testing of equipment. 
Monitor and organise calibration of equipment. 
ESD coordination, purchasing equipment, test station monitoring, compliance, generating ESD checklists, ESD prep and grounding of workbenches and equipment and providing ESD training where required.
Assist with soldering, kit building, workstation layout, designing jigging and fixtures.
Organise shipping and receiving of parts to/from suppliers and manufacturers. 
Create Risk Assessments & COSHH forms.  
Skills & Experience: 

Bachelor’s in Electrical and Electronic Engineering, Computer Science or a similar field OR 5 years of working in a test lab experience, ideally at Technician level.
Experience handling optical fibres and optoelectronic devices.
Operating advanced test and measurement communication network equipment.
PCB design, soldering, etc.
Python/C/Matlab programming.
Linux and Software for HPC/AI node/server operations.
Network configuration.What’s in it for you?

Up to £50k DOE
Lucrative stock options.
25 days holiday + bank holidays + Xmas & New Years shutdown.
Hybrid working.
Relocation assistance.
Visa sponsorship provided

Related Jobs

View all jobs

Research Scientist

Integrator Eng

Machine Learning Engineer/Researcher - 2025 Programme

Senior Data Scientist

AI Engineering Researcher

Deep Learning Researcher

National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.