Performance Analysis Engineer

arm limited
Cambridge
8 months ago
Applications closed

Related Jobs

View all jobs

Connectomics Data Analysis Engineer

Powertrain Simulation Engineer

Machine Learning Engineer

Senior IT Engineer

Product Support Engineer

Senior Aerodynamics Engineer

The Role

Job Overview:

We are looking for a cunning champion in software engineering with a strong analytical mindset to join the team and help ensure the best ML performance with most recent Arm ML software, systems and IP.

The successful engineer will be highly flexible, quick to learn and be motivated by the opportunity to understand and improve the performance of future Machine Learning solutions using Arm technology.

Are you our next team member?

Responsibilities:

As a member of the ML System Analysis team you will conduct performance analysis investigations to gain insights and help influence the direction of Machine Learning software. We work in small teams, so your contributions will make a difference.

You will engage with specialists across Arm, including software and systems teams to understand, explore and challenge the limits of performance capabilities.

You will use advanced pre-silicon platforms of next-generation systems, to understand new use-cases and significant workloads to ensure Arm IP and systems deliver excellent ML performance.

Required Skills and Experience :

Experience with SW development in languages such as Python, C, C++ A passion for analysis and improvements. Strong communication skills, inter-cultural awareness and you embrace diversity. Ability to distil and pick out key findings from large amounts of data.

“Nice To Have” Skills and Experience :

Experience with pre-silicon platforms such as Models, RTL simulation, emulation or FPGA. Data analysis and visualisation, for example Jupyter Notebooks

In Return:

At Arm, you will enjoy working in a highly stimulating collaborative environment. Our team works closely with other software, hardware and system teams across the company.

You will have a chance to share ideas with and learn new skills from the best engineers in the world. We work in small teams, so your contributions will really make a difference.

#

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.