Every day, millions of organizations - from businesses to public institutions - rely on Amazon Business for the procurement of the products they need to fulfil their mission.

The Amazon Business Search team sits at the heart of that experience. We´re redefining how over eight million B2B customers search, navigate, and discover products through conversational search, autocomplete, and intelligent navigation systems.

As a Machine Learning Engineer on our engineering team, you will design and build the next generation of Search and Discovery infrastructure that powers Amazon´s B2B marketplace. You´ll work at the intersection of large-scale distributed systems and GenAI, partnering closely with Applied Scientists to bring LLMs and agentic models into production.

This is a unique opportunity to push the boundaries of search technology, improve relevance for millions of customers worldwide, and help shape the future of B2B commerce.

Key job responsibilities

- Design, develop, and deploy ML-powered search components that improve result relevance, query understanding, and autocomplete quality - with a focus on scalability, inference performance optimization, and efficient use of compute resources.

- Own the full software development lifecycle, including design, implementation, testing, experimentation, and maintenance, ensuring high reliability and measurable customer impact.

- Build and optimize data and model-serving pipelines to support high-throughput, low-latency applications across distributed systems.

- Collaborate across Product, Software, and Science teams to deliver complex projects at scale, while mentoring and guiding peers on latest ML and AI technologies and best practices.

About the team

We are a two-pizza team of software engineers based in Madrid, building the next generation of Amazon Business Search. Our team is international and inclusive, bringing together diverse perspectives to solve complex technical challenges.

We value fast learners, problem solvers, and innovators who take ownership from concept to delivery. We work backwards from the customer, combining strong business awareness with deep technical expertise. Our culture is agile and experimentation-driven - we move quickly, measure impact, and continuously improve to deliver world-class search experiences for millions of B2B customers.

BASIC QUALIFICATIONS

- Bachelor´s degree in computer science or equivalent

- Experience in professional, non-internship software development

- Experience in machine learning, data mining, information retrieval, statistics or natural language processing

- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design

- Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch

- Knowledge of cloud computing services or deployment architecture

- Experience building, deploying, and maintaining large-scale machine learning infrastructure using distributed data processing frameworks such as Spark or Ray

PREFERRED QUALIFICATIONS

- Master´s degree in computer science or equivalent

- Expertise in large-model inference optimization, including techniques such as quantization, pruning, and distillation

- Experience with LLM inference frameworks (e.g., vLLM, DeepSpeed, Hugging Face Transformers)

- Demonstrated experience designing semantic search or RAG pipelines, integrating embeddings, vector stores, and generative models

- Proficiency in online and offline experimentation, evaluation frameworks, and metrics instrumentation for ML systems

- Strong collaboration and communication skills, with the ability to bridge science and engineering to deliver end-to-end ML solutions

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. Protecting your privacy and the security of your data is a longstanding top priority for Amazon.