SoC Validation Engineer, Amazon Devices

Amazon
London
1 month ago
Applications closed

The team that built the innovative Silicon IP AZ1 Neural Edge that is powering the latest generation of Echo devices is looking for an SoC Emulation Engineer to continue to innovate on behalf of our customers. We are a part of Amazon Lab126 that revolutionized reading with our Kindle family of products and reimagined user experience through Echo and Alexa. We want you to help us build on the success of our first generation of ML accelerator at edge.

Work hard. Have fun. Make history.

Key job responsibilities

As an SoC Validation Engineer, you will be responsible for enabling the pre-silicon and post-silicon validation verification of next generation SoCs on multiple platforms such as emulation, prototyping and early silicon. You will develop and execute test plans, design test environments and help build emulation and prototype models while working closely with architects, RTL designers, SoC and software development teams.

BASIC QUALIFICATIONS

  1. Bachelor’s degree or higher in EE, CE, or CS
  2. 3+ years experience in pre-silicon verification using SystemVerilog/UVM
  3. 3+ years’ experience in post-silicon validation
  4. Very strong problem solving, debug and analysis, and automation skills
  5. Experience with verification and validation of complex SOCs
  6. Solid grasp of concepts of HW/SW interface
  7. Strong programming skills (assembly, C, Perl/Python)
  8. Firsthand experience with silicon bringup, complex system debug, or bare-metal programming.

PREFERRED QUALIFICATIONS

  1. Experience in a full development cycle from pre-silicon verification to silicon bringup
  2. MS or PhD in Computer Science, Electrical Engineering or related field
  3. Experience with ARM and various DSP ISA
  4. Experience with SOC fabrics, memory controllers, and SOC peripherals
  5. Experience with machine learning, computer vision or robotics
  6. Excellence in technical communication with peers and non-technical cohorts

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

#J-18808-Ljbffr

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.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.