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

Nominate & Attend

Software Development Engineer , AWS Payments

Amazon
London
3 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer III - Data Engineer - Python, SQL - Senior Associate

Software Engineer II - Data Engineer, Python, SQL - Associate

Data Engineer

Machine Learning Engineer

Staff Data Engineer

Data Engineer

Software Development Engineer, AWS Payments

Machine learning, big data; real-time data streaming. If these areas resonate with you, then join us to work on extremely motivating challenges at Amazon Web Services (AWS). Within AWS Payments we build and run Machine Learning models to optimize business processes and improve the customer experience.

If you are a strong software engineer, self-starter and learner who is passionate about working with massive amounts of data to build state-of-art systems on top of AWS native services, then this is the right opportunity for you. You will work with a team of highly skilled engineers and scientists to build the next generation Machine Learning, Data, and Analytics platform at AWS. As part of your job, you will deal with large amounts of training data, rapid prototyping of new models, performance optimizations, offline and online testing, and building fully automated solutions to push Machine Learning models to production, applying MLOps best practices.

As a software development engineer of this team, you will play a pivotal role in shaping the definition, vision, design, roadmap and development of this set of product features from beginning to end. You will:

  1. Mentor and lead junior developers on the team.
  2. Help drive business decisions with your technical input.
  3. Design, implement, test, deploy and maintain innovative software solutions, while optimizing service performance, durability, cost, and security.
  4. Use software engineering best practices to ensure a high standard of quality for all of the team deliverables.
  5. Participate in the full development cycle for ETL: design, implementation, validation, documentation, and maintenance.
  6. Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Glue/lake formation, EMR/Spark/Scala, Athena etc.
  7. Write high quality distributed and scalable systems, to deal with large scale data.
  8. Automate the end-to-end development life-cycle to deploy Machine Learning models from research phase to production.
  9. Work in an agile, startup-like development environment, where you are always working on the most important stuff.
  10. Work closely with scientists, data engineers and other stakeholders to create and deploy new features, in order to optimize various business processes.


In this role you will contribute to a critical and highly-visible function within the AWS business. You will be given the opportunity to autonomously deliver the technical direction of new projects and features in our roadmap. If you’re excited to have a large impact on AWS and the cloud computing industry, you’ll find this role to be engaging, challenging, and full of opportunities to learn and grow.

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

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
- Experience building and optimizing ‘big data’ pipelines, architectures and data sets
- Experience using big data technologies (Hive, Hbase, Spark, EMR, etc.)
- Advanced working SQL knowledge and experience working with relational databases

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, disability, age, 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.

The base salary for this position ranges from $114,800/year up to $191,800/year. Salary is based on a number of factors 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. Applicants should apply via our internal or external career site.

#J-18808-Ljbffr

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.

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.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.