Senior Applied Scientist, Rufus Features Science

At Amazon, we're revolutionizing the future of shopping with Rufus, our AI-driven shopping assistant. We're seeking an exceptional Senior Applied Scientist with a strong machine learning, NLP and Gen AI background with relevant industry experience to join our Rufus Features Science team in London. You will work at the intersection of the latest research and real-world impact, pushing the boundaries of agentic AI, multimodal language technology, leveraging RAG and RL, to create unparalleled shopping experiences. As a Senior Applied Scientist, you'll be at the forefront of developing state-of-the-art, conversation-based, agentic, multimodal shopping experiences. You will leverage the latest advancements in Multimodal and Visual Large Language Models (MLLMs/VLMs), and AI Agents to transform how customers discover, research, and purchase products.

As a Senior Applied Scientist at Amazon, you'll set the standard for scientific excellence, make decisions that influence our algorithm and architecture development, and drive innovation in agentic MLLM technology. Your work will directly enhance how customers interact with our platform, making product discovery and purchasing more intuitive, efficient, and personalized. If you're passionate about pushing the boundaries of AI, thrive in solving complex problems, and want to make a significant impact on the e-commerce industry, we want to hear from you.

Key job responsibilities
* Lead the development of state-of-the-art agentic LLM solutions for conversational shopping, considering scalability, latency, and quality.
* Design and implement innovative AI technologies that push the boundaries of Natural Language Processing (NLP), Generative AI, MLLMs/VLMs, Machine Learning (ML), Retrieval-Augmented Generation (RAG), and Reinforcement Learning (RL).
* Lead science roadmaps spanning multiple areas, working with senior leaders and stakeholders.
* Develop and evaluate production Agentic AI systems for real customer use cases, focusing on LLM-based conversational interfaces and multimodal interactions.
* Drive end-to-end MLLM projects with high ambiguity, scale, and complexity, taking a hands-on approach to the most critical aspects.
* Collaborate with cross-functional teams to rapidly bring new research into production, directly impacting millions of customers.
* Communicate progress and results internally to both technical and non-technical audiences and publish at top-tier conferences.

About the team
You will be part of the Rufus Features Science team based in London, working alongside over 100 engineers, designers and product managers, focused on shaping the future of AI-driven shopping experiences at Amazon. This team works on every aspect of the shopping experience, from understanding multimodal user queries to planning and generating MLLM responses that combine text, image, audio and video.

Basic Qualifications

- PhD
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with neural deep learning methods and machine learning
- Experience in building machine learning models for business application
- PhD in NLP, Information Retrieval, Machine Learning, or related fields (or equivalent experience), with 6+ years of industry experience.
- Extensive experience with deep learning-based NLP, IR, and MLLM/VLM methods.
- Strong track record in addressing real-world problems using ML and NLP.
- Expertise in developing and owning production ML models and systems, particularly those involving LLMs.
- Proficiency in Python and experience with production-level implementation.
- Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
- Familiarity with cloud computing platforms, particularly AWS.
- Demonstrated ability to lead and shape scientific roadmaps across multiple areas, collaborating with product, science, and engineering managers.
- Knowledge of recent advancements in AI agents, including multi-agent systems and agent evaluation frameworks.

Preferred Qualifications

- Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Good publication record at top-tier venues such as ACL, NAACL, EMNLP, SIGIR, ICLR, NeurIPS, or similar.
- Understanding of e-commerce and recommendation systems.
- Excellent communication skills, solid work ethic, and a strong desire to write production-quality code.

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. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.