Amazon Development Center (Romania) S.R.L.
Technology
AppliedScientist
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Applied Scientist at Amazon Development Center (Romania) S.R.L.. Skills: NLP, Multi-modal modeling, Large language model, Machine learning. Research and Evaluate state-of-the-art algorithms. Design new algorithms”
What You'll Achieve.
Improve safety and compliance mechanisms; Achieve best-in-class standards; Drive business impact
Industry & Context.
Solve problems creatively; Measure and estimate risks
What They're Looking For.
Must Have
Master's degree and experience in CS, CE, ML or related field, Experience in algorithms and data structures, Experience in parsing, Experience in numerical optimization, Experience in data mining, Experience in parallel and distributed computing, Experience in high-performance computing, Experience with Python, Experience with Java, Experience with C++, Experience building machine learning models, 5+ years neural deep learning methods, 5+ years machine learning
Nice to Have
PhD, Experience with statistical modeling, Experience with machine learning, Experience in professional software development, Experience implementing algorithms using toolkits, Experience implementing algorithms with self-developed code, Experience in patents, Experience in publications at top-tier peer-reviewed conferences, Experience in publications at top-tier peer-reviewed journals, Experience working cross functionally across several teams
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
Contribute to the research roadmap
Contribute to the product roadmap
Collaborate with other scientists
Collaborate with engineers
Collaborate with product managers
Collaborate with business teams
Solve problems creatively
Measure and estimate risks
Critique peer research constructively
Consult with engineering teams
Design data pipelines
Design modeling pipelines
Publish research publications
How You'll Work.
Team & Collaboration
Cross functionally across several teams; With engineers; With technical program managers; With product managers; With other scientists; With business 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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