Machine Learning Software Technology Manager

Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineering Manager, Gen AI

AI Engineer / Machine Learning Engineer

Senior Machine Learning Engineer

Software Engineer III - MLOps

Lead Software Engineer - MLOps

Data Scientist Manager

Job Overview:

As a Software Technology Manager, you will work with Arm's key customers to define and prioritise requirements for software enablement and optimization and to develop strategies to deliver them working within Arm and our software ecosystem!

 

Our Machine Learning group is our centre of excellence for all AI and ML on Arm's CPUs, GPUs, and dedicated accelerators. You will be part of our team of technology managers who are addressing the growing demand for Machine Learning on Arm technology.

 

We are responsible for the roadmap and vision for our software development, configuration, optimization, plus productisation and delivery activities. We develop strategies around new and existing software components to support Arm's products.

 

We gather use-cases and requirements for how software solutions can fulfil the needs of complex systems. We engage with open-source communities and communicate the opportunities of open-source software. We create product plans to ensure Arm's software solution products are successfully deployed to our partners across multiple market segments. Our knowledge of software communities, development practices and release methodologies enable us to match the lifecycle of our hardware products to build and deliver complete product solutions.

 

We work closely with Project Managers, Architects, Engineering Leads and Product Managers internal and external to Arm. Together, we collaborate to deliver the best software for Arm's technology and communicate its value to the world!

Responsibilities:

Evaluate the complete value chain of end customers, manufacturers, and designers of hardware, software, and systems. This includes productisation, support and quality assurance relating to what we deliver to those customers.

Gather specific market segment needs and translate these into product plans.

Work with internal engineering teams and partner software vendors to prioritize features and enhancements meeting customer needs.

Perform competitive analysis to identify the strengths and weaknesses of Arm-based solutions versus the competition.

Evangelize in open-source communities and enthuse our partners with the software offering by participating in customer meetings and training.

Required Skills and Experience :

Demonstrable experience with management of software requirements (preferably in a software product delivery context), and an understanding of how they are validated and delivered to required levels of quality.

Ability to express ideas and communicate effectively with other team members, customers, and suppliers to formulate, agree, and implement strategic plans.

Software development experience

Motivation to work unsupervised, but as an integral member of a local developer team, as well as our globally distributed technology management team.

Comfortable with the requirement to travel occasionally.

“Nice To Have” Skills and Experience :

Good university degree (or equivalent), ideally in a numerate subject, although other graduates would be considered if they have relevant experience.

Visibility or experience of a full open-source software development lifecycle and the components of a typical software stack. This could include definition of non-functional aspects of software and targets for integration maturity.

Experience with the definition of requirements to achieve quality and optimisation goals.

Work in software performance.

In Return:

You will get to utilise your engineering skills to build support for the technologies in millions of devices for years to come!

 

#LI-JB1

 

Accommodations at Arm

At Arm, we want our people to Do Great Things. If you need support or an accommodation to Be Your Brilliant Self 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 requests will be treated with confidentiality, and information concerning these requests will only be disclosed as necessary to provide the accommodation. Although this is not an exhaustive list, examples of support include breaks between interviews, having documents read aloud or office accessibility. Please email us about anything 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 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. Within that framework, we empower groups/teams to determine their own hybrid working patterns, depending on the work and the team’s needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this 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 of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don’t discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status 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.