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

Apply Now

Software Development Engineer - GenAI, Amazon Ads - Creative X

Amazon
London
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer - Machine Learning

Test Data Engineer

Lead Data Engineer (Data Science Team)

AI/MLOps Platform Engineer

AI/MLOps Platform Engineer

AI/MLOps Platform Engineer

Software Development Engineer - GenAI, Amazon Ads - Creative X

Job ID: 2906498 | Amazon Development Centre (Scotland) Limited

Shape the future of Generative AI at Amazon! Join our team building the infrastructure and platforms that power next-generation AI capabilities used by thousands of developers across Amazon's products and services.

Be part of a dynamic team bridging advanced AI research with real-world applications. We're looking for passionate engineers to create tools and platforms that accelerate AI innovation while maintaining the highest standards of security and scalability.

Key Highlights:

  1. Work directly with AI researchers and scientists to transform innovative ideas into production systems
  2. Build and own critical infrastructure powering Amazon's next-generation AI capabilities
  3. Create developer platforms and tools that accelerate AI innovation
  4. Drive the future of ethical and sustainable AI development
  5. Work with advanced technologies including AWS Bedrock, SageMaker, and custom MLOps tools

What You'll Do:

  1. Design and implement scalable, production-ready AI infrastructure and platforms
  2. Create intuitive tools and interfaces for AI model deployment and management
  3. Build robust APIs and services that enable AI capabilities across Amazon
  4. Collaborate with science teams to optimize AI development workflows
  5. Ensure security, scalability, and operational excellence of AI systems

Why You'll Love It:

  1. Impact: Your work will directly influence how AI capabilities are developed and deployed at Amazon
  2. Innovation: Work at the intersection of advanced AI research and enterprise-scale engineering
  3. Growth: Learn from experts while working with the latest in AI technology
  4. Purpose: Help shape responsible AI development practices and sustainable computing
  5. Team: Join a collaborative environment focused on solving complex, meaningful challenges

This role offers unique exposure to both AI infrastructure and product development, positioning you to make significant contributions to Amazon's AI initiatives while working with some of the industry's brightest minds.

Key Job ResponsibilitiesTechnical Leadership

  1. Design and build scalable AI infrastructure and MLOps platforms
  2. Lead technical design discussions for medium to large-scale projects
  3. Own full software development lifecycle from design to production
  4. Make architectural decisions that balance innovation with operational excellence

Development & Implementation

  1. Create secure APIs and services that expose AI capabilities
  2. Build developer tools and interfaces for AI model deployment
  3. Implement monitoring and observability solutions
  4. Write high-quality, well-tested code following best practices

Technical Collaboration

  1. Work with science teams to understand and deliver technical requirements
  2. Partner with product teams to integrate AI capabilities
  3. Mentor junior engineers and contribute to code reviews
  4. Participate in on-call rotation for production support

Innovation & Operations

  1. Drive continuous improvement of existing systems and processes
  2. Ensure solutions meet security and performance standards
  3. Contribute to technical roadmap and strategic planning
  4. Champion sustainable and ethical AI development practices

BASIC QUALIFICATIONS

  1. Experience in professional, non-internship software development
  2. Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
  3. Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence

PREFERRED QUALIFICATIONS

  1. Bachelor's degree or equivalent

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.

#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.

Jobs

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Jobs

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.