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A global technology firm is seeking an Applied Scientist to join their Compliance and Safety Services team in Torino, Italy. The successful candidate will utilize state-of-the-art NLP and machine learning techniques to enhance product compliance and safety standards. Responsibilities include researching algorithms, designing new solutions, and collaborating with cross-functional teams. Candidates should have a PhD or Master's with experience in machine learning, and programming skills in Python, Java, or C++. This role offers a unique opportunity to shape compliance solutions at a leading company.
Job ID: 3147629 | Amazon Development Center (Romania) S.R.L.
Amazon's Compliance and Safety Services (CoSS) Team is looking for a smart and creative Applied Scientist to apply and extend state-of-the-art research in NLP, multi‑modal modeling, domain adaptation, continuous learning and large language model to join the Applied Science team. At Amazon, we are working to be the most customer‑centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to drive research that will shape new ML solutions for product compliance and safety around the globe in order to achieve best‑in‑class, company‑wide standards around product assurance.
You will research on large amounts of tabular, textual, and product image data from product detail pages, selling partner details and customer feedback, evaluate state‑of‑the‑art algorithms and frameworks, and develop new algorithms to improve safety and compliance mechanisms. You will partner with engineers, technical program managers and product managers to design new ML solutions implemented across the entire Amazon product catalog.
As an Applied Scientist on our team, you will:
The science team delivers custom state‑of‑the‑art algorithms for image and document understanding. The team specializes in developing machine learning solutions to advance compliance capabilities. Their research contributions span multiple domains including multi‑modal modeling, unstructured data matching, text extraction from visual documents, and anomaly detection, with findings regularly published in academic venues.
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