Requirements

Operating system

Windows

Linux

Our requirements

• Strong knowledge of deep learning and language model architectures (Transformers).
• Hands-on experience with deep learning frameworks (preferably PyTorch) and AI models training frameworks like Axolotl, Ms-Swift, trl, PEFT.
• Solid understanding and hands-on experience with classical machine learning and natural language processing methods.
• Demonstrated expertise in at least one programming language: Python or C/C++.
• Good fluency in using the Linux environment and creating shell scripts.
• Experience in building scalable data pipelines, dataset curation, and performance monitoring for AI systems.
• MSc or PhD in Computer Science, Mathematics, or a related technical field (or equivalent R&D experience).
• Ability to conduct scientific literature reviews and translate cutting-edge research into production-ready solutions.
• Keeping up to date with technological innovations in the field of AI/NLP, participation in AI-related conferences.
• Minimum 2 years of experience in Natural Language processing, preferred with advanced neural models.

Optional

• Research experience, publications in the area of NLP or machine learning. Track record in top AI/ML conferences (NeurIPS, ICLR, ICML, CVPR, ACL) is a great advantage.
• Experience in using cloud services (AWS, GCP, Azure).
• Experience in web crawling, web parsing, information retrieval, information extraction, knowledge bases building or Big Data projects.
• Recognized achievements in AI competitions or algorithmic challenges.
• AI Knowledge: Experience with AI-driven solutions for data augmentation, synthetic data creation or agentic frameworks and multi-agent workflows.
• Professional experience in developing product-grade code, including high-level software development practices, integration into CI environments, proper testing, packaging, and releasing of software.

Your responsibilities

• Design and implement systems based on advanced AI like LLMs, encoder-based language models, Agentic AI, to analyze large textual or multimodal data sets.
• Automate processes like quality data collection, multi-gpu model training, post-training stack like PEFT or RLHF, processing pipelines and performance monitoring.
• Applying best practices from the fields of classical machine learning and NLP in systems that use generative AI to enhance its performance and supervise it.
• Creating prototypes as well as internal and commercial solutions for Samsung products, including Big Data systems and on-device solutions.
• Conduct scientific literature reviews and implement state-of-the-art technology into new products.
• Contribute to creating innovative products, scientific publications, lectures, workshops, international contests, and patent applications.
• Collaboration with external experts and overseas R&D centers. Intensive partnership with a team of language experts in the creation of data sets.
• Collaborate closely with product management to define product strategy and roadmap.