Applied Scientist Manager, EU InTech, Item data Quality (IDQ)
DESCRIPTION
At Amazon, we are committed to being the Earth’s most customer-centric company. The International Technology group (InTech) owns the enhancement and delivery of Amazon’s cutting-edge engineering to all the varied customers and cultures of the world. We do this through a combination of partnerships with other Amazon technical teams and our own innovative new projects.
You will be joining the Tools and Machine learning (Tamale) team. As part of InTech, Tamale strives to solve complex catalog quality problems using challenging machine learning and data analysis solutions. You will be exposed to cutting edge big data and machine learning technologies, along to all Amazon catalog technology stack, and you'll be part of a key effort to improve our customers experience by tackling and preventing defects in items in Amazon's catalog.
We are looking for a passionate, talented, and inventive Applied Scientist Manager (ASM) with a strong machine learning background and people development skills. As an ASM you will lead a team of scientists, leading projects impacting Amazon's catalog WW. You will guide your team's work, coaching and professional growth. Plus, you will partner closely with a strong engineering team to productionalise your solutions.
We strongly value your hard work and obsession to solve complex problems on behalf of Amazon customers.
Key job responsibilities
We look for applied scientists managers who possess a wide variety of skills. As the successful applicant for this role, you will with work closely with your business partners to identify opportunities for innovation. You will lead a team to apply machine learning solutions to automate manual processes, to scale existing systems and to improve catalog data quality, to name just a few. You will work with business leaders, scientists, and product managers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services. You will lead a team of scientists and work closely with an engineering team working on solving data quality issues at scale. You will be able to influence the scientific roadmap of the team, setting the standards for scientific excellence. You will be working with state-of-the-art models, including image to text, LLMs and GenAI.
Your work will improve the experience of millions of daily customers using Amazon in Europe and in other regions. You will have the chance to have great customer impact and continue growing in one of the most innovative companies in the world. You will learn a huge amount - and have a lot of fun - in the process!
This position will be based in Madrid, Spain
BASIC QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
- 3+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Experience with leading a science team required
- Experience with building large scale deep learning solutions for business required
- Experience programming in Java, C++, Python or related language required
PREFERRED QUALIFICATIONS
- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience with building and managing a science team required.
- Experience with leading a science team to conduct applied research in a large scale and dynamic corporate setting required.
- Strong track record of scientific publications at top-tier peer-reviewed conferences or journals required.
- Highly skilled at cross-functional collaborations including ability to communicate with diverse audiences, deal ambiguities and resolve issues required.
- Experience with deep learning modeling tools and workflows such as MxNet, TensorFlow, scikit-learn, Spark MLLib, numpy, scipy etc required.
- Experience with LLM model training and fine-tuning desired
- Experience with deep learning modeling techniques including Transformers required.
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