Computer Vision Engineer

Arm Limited
Manchester
4 days ago
Create job alert

We are looking for experienced engineers with a hands-on machine learning background, and good understanding of graphics and gaming, to develop new neural graphics algorithms.

Job Overview:

In Arm's Central Technology group we are building trail-blazing future technology which will keep Arm-based products redefining the state-of-the-art. We are looking for experienced ML Engineers who will build a range of innovative algorithm solutions, aimed to guide architecture definition of the next-gen Arm compute platforms.

You will be working in a team of computer vision and machine learning engineers to prototype algorithms for graphics (gaming) that pushes the state of the art.

Responsibilities:
  • Inventing and implementing state of the art machine learning and graphics algorithms for gaming use cases
  • Designing such algorithms to work reliably and efficiently on mobile devices
  • Collaborating with other teams across software and hardware to ensure the full pipeline runs efficiently and utilises Arm hardware effectively
  • Presenting the algorithms and architectures you have developed to wider technology and engineering teams within Arm and at external events/conferences
Required Skills and Experience:
  • Strong experience working on high-performance deep learning models for image processing and computer graphics
  • Excellent coding skills in python and strong experience in popular ML framework (e.g. TensorFlow or PyTorch)
  • Excellent problem solving and analytical thinking skills
  • Excellent communication and collaboration skills
  • Passion for deep learning, graphics, and image processing
Nice To Have Skills and Experience:
  • Technical leadership experience
  • Understanding of the graphics rendering pipeline and familiarity with graphics on mobile GPUs
  • C++ experience and familiarity with Shading languages
  • Experience in 3D gaming, lighting and rendering is a plus
  • Image/video quality evaluation background
In Return:

On top of the already compelling life at Arm, we offer strong team culture, learning opportunities, regular career conversations, emphasis on diversity, equity and inclusion and a continuous improvement mentality.

Accommodations at Arm

At Arm, we want to build extraordinary teams. If you need an adjustment or an accommodation during the recruitment process, please email . To note, by sending us the requested information, you consent to its use by Arm to arrange for appropriate accommodations. All accommodation or adjustment requests will be treated with confidentiality, and information concerning these requests will only be disclosed as necessary to provide the accommodation.

Hybrid Working at Arm

Arm’s approach to hybrid working is designed to create a working environment that supports both high performance and personal wellbeing. We believe in bringing people together face to face to enable us to work at pace, whilst recognizing the value of flexibility.

Equal Opportunities at Arm

Arm is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues.


#J-18808-Ljbffr

Related Jobs

View all jobs

Computer Vision Engineer

Senior Data Research Engineer Computer Vision

Senior Computer Vision Engineer - up to £70,000 - ID44602

Senior Computer Vision Engineer

Senior Computer Vision Engineer

Senior Computer Vision Engineer...

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.