Senior Software Engineer - Machine Learning Tools - Innovative cross-platform technology development (Apply in minutes)

ARM
Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Senior MLOPs Engineer

Senior Simulation Engineer (Data Science)

Lead Software Engineer (Machine Learning)

Senior Machine Learning Engineer, Gen AI

Senior Machine Learning Engineer

Machine Learning Engineer Python AWS

The world’s software is built on Arm technology, and as such it is essentialthat we meet developers where they work – ensuring that the best developerexperiences are on Arm platforms and that the full power of Arm’s technologyis easily available for those developers to consume.## **Job Overview:**In the Developer Platforms group at Arm, our mission is to make softwaredevelopment on the Arm architecture simple and intuitive. We are growing ourteam and are looking for a passionate software engineer to help us buildstreamlined machine learning experiences for developers.Our team solves a diverse set of developer challenges, delivering tools thatsupport application distribution, toolchain setup and configuration, profilingand debug, and visualisation.This is a unique opportunity to work on many different technologies in a groupdelivering tools across multiple platforms including desktop and browser.##Responsibilities:* Work as part of a diverse team to design, deliver and refine the tools and experiences required to support development on Arm processors * Work alongside peers and junior team members to solve technical problems, mentoring as necessary * Form effective relationships with other engineers, product managers and UX specialists to enable collaboration and best understand and empower our users. * Engage with our agile planning and development processes to help shape delivery of our products * Demonstrate quality through unit testing and continuous integration## **Required Skills and Experience :**We are seeking an experienced engineer with the following skills: * Proven experience working with machine learning models and an understanding of their architecture, optimisation techniques, deployment and librariesruntimes * Familiarity with the basics of modern, effective software development: source control, automated testing, object-oriented or functional paradigms and the Agile methodology. * A get things done attitude to shipping high-quality, robust software which is maintainable and responsive to evolving requirements. * A passion to push forward the state of the art in developer tooling by embracing new technologies and continuous innovation## **“Nice To Have” Skills and Experience :**Any experience with the technologies listed below is beneficial, however, adesire to learn is far more valuable than experience in any tool, and weactively support ongoing training. * Experience working with an existing machine learning library codebase (e.g. PyTorch) * Strong Python or TypeScript skills, specifically around user interfaces * Continuous integration and delivery workflows including source control management, build systems, testing and deployment * Experience with Agile & UX design principles and processes## **In Return:**You will join an established and experienced team working with innovativetechnologies in an agile environment which requires proactivity, dynamicapproaches to problem solving and creative thinking.You will work on greenfield software products which ship with new Arm hardwareon day one.Please provide a covering letter on application.#LI-JB1##Accommodations at ArmAt 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 ArmArm’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 ArmArm 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 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.

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.

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.