Amazon Development Center (Romania) S.R.L.

Administrative Support, Applied Science, no business category

AppliedScientist

€72–108k ~AI est. Bucharest, Romania FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Applied Scientist at Amazon Development Center (Romania) S.R.L.. Skills: NLP, Machine learning, Large language models. Research and evaluate state-of-the-art algorithms. Design new algorithms”

What You'll Achieve.

Improve safety and compliance mechanisms; Develop better approaches; Improve product assurance; Improve customer trust

Industry & Context.

Administrative Support, Applied Science, no business category
Problems you'll solve

Solve problems; Measure risks; Estimate risks

What They're Looking For.

Must Have

Experience programming in Java, C++, Python, Bachelor's degree or above in Engineering, Computer Science, Machine Learning, Statistics, Physics, or related fields, Experience building machine learning models or developing algorithms for business application

Nice to Have

Experience in professional software development, Experience implementing algorithms using toolkits and self-developed code, Experience in patents or publications at top-tier peer-reviewed conferences or journals, Experience working cross functionally across several teams, Experience with modeling tools such as scikit-learn, PyTorch, numpy, scipy

What You'll Do.

Research and evaluate state-of-the-art algorithms

Design new algorithms

Design and plan collection of new labels

Design audit mechanisms

Analyze and convey results to stakeholders

Contribute to research and product roadmap

Collaborate with other scientists

Consult with engineering teams to design data and

Publish research publications

How You'll Work.

Team & Collaboration

Partner with engineers; Partner with technical program managers; Partner with product managers; Collaborate with other scientists; Collaborate with engineers; Collaborate with product managers; Collaborate with business teams; Consult with engineering teams

Communication Scope

Convey results to stakeholders

Full Job Description

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. Key job responsibilities As an Applied Scientist on our team, you will: - Research and Evaluate state-of-the-art algorithms in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model. - Design new algorithms that improve on the state-of-the-art to drive business impact, such as synthetic data generation, active learning, grounding LLMs for business use cases - Design and plan collection of new labels and audit mechanisms to develop better approaches that will further improve product assurance and customer trust. - Analyze and convey results to stakeholders and contribute to the research and product roadmap. - Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research - Consult with engineering teams to design data and modeling pipeline

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