National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Staff Software Engineer, Machine Learning Performance

Google
London
9 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Performance Engineer

Staff Machine Learning Engineer

Machine Learning Performance Engineer

Machine Learning Engineer (London)

Machine Learning Engineer (W/M/D)

Software Engineer

Minimum qualifications: - Bachelor's degree or equivalent practical experience. - 8 years of experience in software development and with data structures/algorithms. - 5 years of experience with AI/ML algorithms and tools, LLMs or other multimodal foundation models, and natural language processing. - 5 years of experience in distributed development and large-scale data processing. - Experience coding in C++ or Python. Preferred qualifications: - Experience in performance analysis and optimization, including system architecture, performance modeling, or similar. - Experience working in a complex, matrixed organization involving cross-functional, or cross-business projects. - Experience in a technical leadership role leading project teams and setting technical direction. - Experience debugging large model performance in training or serving (e.g., ML Framework like JAX, TF, PyTorch). - Experience in Graphics Processing Units (GPUs), TPUs or other hardware accelerators. - Experience in ML system development. Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. In this role, you will collect and analyze profile data and provide expert-level visualizations and user actionable advice. You will serve high impact opportunities within Alphabet (e.g., improving Large Language Models (LLMs), guiding TPU chip co-design) and cross-industry supporting new frameworks and chips to run in different cloud environments. Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. - Drive continuous improvements to the machine learning software/hardware stacks through providing insightful performance debugging. - Provide insights by summarizing different views of captured profile data such as trace timelines, memory usage, High-level Operations (HLO) profiles, Machine learning (ML) graph summaries. - Learn and build an intuitive understanding of existing data collection, analysis, and visualization workflows. - Support new, exciting ML paradigms such as horizontal scaling for upcoming Tensor Processing Unit (TPU) chips by making contributions across the JAX, compilers stack and analysis tools. - Partner with product area leads, cloud customers to understand model optimization use cases, drive cross-functional efforts to deliver on chip profiling requirements, and propose new hardware features. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See alsohttps://careers.google.com/eeo/andhttps://careers.google.com/jobs/dist/legal/OFCCPEEOPost.pdfIf you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:https://goo.gl/forms/aBt6Pu71i1kzpLHe2.

National AI Awards 2025

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 Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.