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

Nominate & Attend

Sr. Machine Learning Engineer, Amazon General Intelligence (AGI)

Amazon
London
1 week ago
Create job alert

Sr. Machine Learning Engineer, Amazon General Intelligence (AGI)

Job ID: 3003295 | Amazon.com Services LLC - A57

Our Machine Learning training infrastructure (ML Infra) team is responsible for designing, implementing, and optimizing large-scale computing infrastructure that powers our cutting-edge AI and machine learning initiatives. We leverage advanced hardware, innovative software architectures, and distributed computing techniques to enable breakthrough research and product development across the company.

We are seeking a Senior Machine Learning Engineer to join our team and lead the development of our next-generation ML training infrastructure. This is a high impact, high visibility role that will shape the future of our machine learning capabilities and contribute to the advancement of AI technology across the industry.

Key job responsibilities
Lead the definition, design, architecture quality, implementation, and delivery of the most advanced, most difficult, most cross-cutting, and/or most ambiguous challenges spanning across our ML infrastructure.
- Align the teams in ML Infrastructure and related organizations to a coherent technical vision and deliver systems that fit well together.
- Exert influence over multiple teams, increasing their productivity and effectiveness. You hold peers and teams to a high bar for performance and efficiency, and aid teams through your expert guidance and example.
- Considered to be an authority on technical issues by both the technical and research community, you are responsible for guiding difficult trade-off decisions and drive awareness about the impact and consequences of technical decisions on AI research and product development.
- Demonstrate significant innovation, creativity, and judgement when solving challenging AI/ML infrastructure problems. Identify future skills needed across your organization and advocate for the development and/or acquisition of those skills to senior leaders. You scout top talent and recruit them to the company.
- Actively mentor senior and Principal engineers, scale yourself by developing and institutionalizing best practices in AI/ML infrastructure and distributed computing across the organization.

A day in the life
8+ years of professional software development experience in distributed systems with emphasis on ML infrastructure
- 8+ years of current programming experience building ML infrastructure using languages such as Python, C++ or Rust
- Hands-on experience with parallel computing platforms such as CUDA, OpenMP, etc
- Deep understanding of AI frameworks such as PyTorch, TensorFlow, and JAX, and their demands on underlying compute infrastructure, memory bandwidth, network interconnect, and storage as scale goes up
- Knowledge of emerging AI hardware accelerators and architectures
- Experience with containerization and orchestration technologies (Docker, Kubernetes)
- Experience with cloud computing platforms (AWS, Azure, GCP) and their offerings

About the team
Join our AGI team and work at the forefront of AI. Collaborate with top minds pushing boundaries in deep learning, reinforcement learning, and more. Gain valuable experience and accelerate your career growth. This is a unique opportunity to create history and shape the future of artificial intelligence.
Mission of the team: We leverage our hyper-scalable, general-purpose large model training and inference systems to develop and deploy cutting-edge sensory AI foundational models that revolutionize machine perception, interpretation and interaction, with humans and with the physical world.

BASIC QUALIFICATIONS

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team

PREFERRED QUALIFICATIONS

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.

Posted:May 27, 2025 (Updated 6 minutes ago)

Posted:June 18, 2025 (Updated 13 minutes ago)

Posted:June 18, 2025 (Updated 25 minutes ago)

Posted:March 20, 2025 (Updated 25 minutes ago)

Posted:June 16, 2025 (Updated 27 minutes ago)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.


#J-18808-Ljbffr

Related Jobs

View all jobs

Sr. Delivery Consultant - Data Scientist, AWS Professional Services Israel...

Sr. Machine Learning Engineer London, UK

Sr. Machine Learning Engineer

Sr. Data Scientist / Machine Learning Engineer - GenAI & LLM

Sr. Data Scientist / Machine Learning Engineer - GenAI

Sr. Data Scientist / Machine Learning Engineer - GenAI

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.