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Applied Scientist (AI)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Applied Scientist (AI) (NLP/multimodal ML): Developing machine learning solutions for product compliance and safety across Amazon’s product catalog with an accent on NLP, multimodal modeling, domain adaptation, continuous learning, and large language models. Focus on designing algorithms, grounding LLMs, creating data and modeling pipelines, and researching product text, images, documents, and customer feedback.
Location: Timisoara, Bucharest, or Iasi, Romania
Company
develops customer-facing services and machine learning solutions for product compliance, safety, and assurance.
What you will do
- Research and evaluate state-of-the-art algorithms in NLP, multimodal modeling, domain adaptation, continuous learning, and large language models.
- Design algorithms for synthetic data generation, active learning, and grounding LLMs for business applications.
- Research tabular, textual, product image, document, selling partner, and customer feedback data.
- Plan label collection and audit mechanisms to improve product assurance and customer trust.
- Collaborate with scientists, engineers, technical program managers, product managers, and business teams to measure risks and shape research and product roadmaps.
- Consult on data and modeling pipelines and publish research at internal and external venues.
Requirements
- PhD, or a master's degree with experience in computer science, computer engineering, machine learning, or a related field.
- 5+ years of experience with neural deep learning methods and machine learning.
- Experience building machine learning models for business applications.
- Knowledge of algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.
- Programming experience with Python, Java, or C++.
- English communication skills are required for collaboration and research publication.
Nice to have
- Experience with statistical modeling and machine learning.
- Professional software development experience.
- Experience implementing algorithms with toolkits and self-developed code.
- Patents or publications at top-tier peer-reviewed conferences or journals.
- Experience working cross-functionally across several teams.
Culture & Benefits
- Work focuses on research contributions in multimodal modeling, unstructured data matching, text extraction from visual documents, and anomaly detection.
- Research findings are regularly published in academic venues.
- Inclusive hiring and workplace accommodation support are available.
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