Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Machine Intelligence Engineer (Apply in minutes)

ARM
Newton
9 months ago
Applications closed

Related Jobs

View all jobs

Asset & Wealth Management - AI / Machine Learning Software Engineer, Marcus Deposits - Vice Pre[...]

AI and Machine Learning Lead – FinTech SaaS

Asset & Wealth Management - AI / Machine Learning Software Engineer, Marcus Deposits - Vice Pre[...]

Asset & Wealth Management - AI / Machine Learning Software Engineer, Marcus Deposits - Vice President - Birmingham

Data Science Manager (Recommendation) - Retail and Luxury

Computer Vision Tech Lead

Job Description:

Arms Machine Learning Group is seeking highly motivated and creative SoftwareEngineers to join the Cambridge-based ML Content, Algorithms and Tools team!

This Machine Learning Engineer role focuses on advancing the field of AI byoptimizing and deploying pioneering models, particularly Large Language Models(LLMs) and Generative AI algorithms. This involves deep analysis of neuralnetworks, optimizing software and hardware, developing innovative solutions,and collaborating with teams to build high-performance AI systems.

Responsibilities :

Your responsibilities involve working with major ML frameworks (PyTorch,TensorFlow, etc.) to port and develop ML networks, optimize and quantizemodels for efficient execution on Arm platforms, and help ensure multiple Armproducts are designed to perform effectively for machine learning. As an in-depth technical responsibility, you will need to deeply understand the complexapplications you analyze and communicate them in their simplest form tocontribute to product designs, allowing you to influence both IP and systemarchitecture.

Required Skills and Experience :

* A background in computer science, software engineering or other comparable skills* Experience training and debugging neural networks with TensorFlow and PyTorch using Python* Understanding, deploying, and optimizing Large Language Models (LLMs) and Generative AI algorithms.* Experience using software development platforms and continuous integration systems* Familiarity with Linux and cloud services* Have a strong attention to detail to ensure use cases you investigate are well understood and the critical areas needing improvement are understood

Nice To Have Skills and Experience :

* Experience of the inner workings of Pytorch, Tensorflow, Executorch and Tensorflow Lite* Experience of developing and maintaining CItesting components to improve automation of model analysis* Good knowledge of Python for working with ML frameworks* Good knowledge of C++ for working with optimised ML libraries* Previous experience of machine learning projects* Experience with deployment optimizations on machine learning models

In Return :

From research to proof-of-concept development, to deployment on ARM IPs,joining this team would be a phenomenal opportunity to contribute to the fulllife cycle of machine learning projects and understand how innovative machinelearning is used to solve real word problems.

Working closely with experts in ML and software and hardware optimisation - atruly multi-discipline environment - you will have the chance to exploreexisting or build new machine learning techniques, while helping unpick thecomplex world of use-cases spanning mobile phones, servers, autonomous drivingvehicles, and low-power embedded devices

#LI-TE!

##Accommodations at Arm

At Arm, we want our people toDo Great Things. If you need support or anaccommodation toBe Your Brilliant Selfduring the recruitment process,please email . To note,by sending us the requested information, you consent to its use by Arm toarrange for appropriate accommodations. All accommodation requests will betreated with confidentiality, and information concerning these requests willonly be disclosed as necessary to provide the accommodation. Although this isnot an exhaustive list, examples of support include breaks between interviews,having documents read aloud or office accessibility. Please email us aboutanything we can do to accommodate you during the recruitment process.

##Hybrid Working at Arm

Arm’s approach to hybrid working is designed to create a working environmentthat supports both high performance and personal wellbeing. We believe inbringing people together face to face to enable us to work at pace, whilstrecognizing the value of flexibility. Within that framework, we empowergroupsteams to determine their own hybrid working patterns, depending on thework and the team’s needs. Details of what this means for each role will beshared upon application. In some cases, the flexibility we can offer islimited by local legal, regulatory, tax, or other considerations, and wherethis is the case, we will collaborate with you to find the best solution.Please talk to us to find out more about what this could look like for you.

##Equal Opportunities at Arm

Arm is an equal opportunity employer, committed to providing an environment ofmutual respect where equal opportunities are available to all applicants andcolleagues. We are a diverse organization of dedicated and innovativeindividuals, and don’t discriminate on the basis of race, color, religion,sex, sexual orientation, gender identity, national origin, disability, orstatus as a protected veteran.

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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.