Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Software Development Engineer , AWS Payments

Amazon
London
7 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

Senior Data Engineer - Scala/Spark

Senior Data Engineer

Senior Data Engineer

Machine Learning Engineer

Weather 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

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 Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.