Machine Learning Engineer, JP Science and Data (Basé à London)

Jobleads
London
2 days ago
Create job alert

Machine Learning Engineer, JP Science and Data

Job ID: 2903212 | Amazon Japan G.K. - A43

We are seeking a Machine Learning Engineer to architect and implement end-to-end machine learning systems that scale across Amazon’s largest vendors. In this role, your primary focus will be on combining strong software engineering principles with machine learning expertise to build robust, production-grade ML platforms and pipelines to support the delivery of advanced analytics and machine learning models for our eCommerce partners as a part of Amazon's new generation of Paid Services.

You will work directly with Applied Scientists to productionize ML models, Software Development Engineers to build scalable infrastructure, Data/BI Engineers to implement scalable ML-ready data pipelines, and Product Managers to drive the roadmap and vision for Paid Services. As a member of the team you will also work with vendors, team members, and internal and external partners to give input into the way we work, how we serve customers, and where we invest in future capabilities.

This position is ideal for candidates with a strong background in software engineering and machine learning systems, demonstrated experience in ML lifecycle management and infrastructure development, and a passion for building scalable ML solutions that drive tangible business impact through our vendor partnerships.

Key job responsibilities

The MLE is accountable for:

  1. Work with scientists to design and develop scalable ML infrastructure that supports model training, deployment, and monitoring across hundreds of vendors.
  2. Implement efficient data pipeline and architectures that enable automated ML workflows for our eCommerce partners.
  3. Build ML debugging and analysis tools to ensure model reliability and performance.
  4. Utilizing Amazon systems and tools to effectively work with terabytes of data.
  5. Partner with product managers to shape the technical roadmap for Amazon’s new generation of Paid Services.

About the team

In this position, you will be part of the JP Science and Data team, consisting of scientists, business intelligence engineers, data engineers, and machine learning engineers, collaborating with Product Managers and Software Developers worldwide. Our current projects touch on the areas of causal inference, representation learning, anomaly detection, forecasting, LLMs and more. As part of working on Paid Services, you will be exposed to all other projects the team works on: we believe that collaboration is paramount, and working in isolation does not lead to a happy team.

We place strong emphasis on continuous learning through internal mechanisms for our team members to keep on growing their expertise and keep up with the state of the art. Our goal is to be primary science team for vendor solutions in Amazon, worldwide.

BASIC QUALIFICATIONS

  • 3+ years of non-internship professional software development experience.
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
  • Experience programming with at least one software programming language.
  • Familiar with the life cycle of a ML model, i.e., trained, customized, tuned and validated ML models that are leveraged in a science application.
  • Strong understanding of statistics and math.

PREFERRED QUALIFICATIONS

  • 3+ 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.

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 this link for more information.

Posted:February 25, 2025 (Updated about 1 hour ago)

#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer · · (Basé à London)

Machine Learning Engineer, Generative AI Innovation Center

Machine Learning Engineer, Ranking Platform New Remote - United Kingdom (Basé à London)

Machine Learning Engineer - Fixed Term Contract (Basé à London)

Machine Learning Engineer, Enterprise (Basé à London)

Machine Learning Engineer, London (Basé à London)

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.

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.

Machine Learning vs. Deep Learning vs. MLOps Jobs: Which Path Should You Choose?

Machine Learning (ML) continues to transform how businesses operate, from personalised product recommendations to automated fraud detection. As ML adoption accelerates in nearly every industry—finance, healthcare, retail, automotive, and beyond—the demand for professionals with specialised ML skills is surging. Yet as you browse Machine Learning jobs on www.machinelearningjobs.co.uk, you may encounter multiple sub-disciplines, such as Deep Learning and MLOps. Each of these fields offers unique challenges, requires a distinct skill set, and can lead to a rewarding career path. So how do Machine Learning, Deep Learning, and MLOps differ? And which area best aligns with your talents and aspirations? This comprehensive guide will define each field, highlight overlaps and differences, discuss salary ranges and typical responsibilities, and explore real-world examples. By the end, you’ll have a clearer vision of which career track suits you—whether you prefer building foundational ML models, pushing the boundaries of neural network performance, or orchestrating robust ML pipelines at scale.