AI Research Scientist

• Carrying out research on deep learning audio
• Evaluating and testing AI and ML models
• Implementing and training models
• Model research, implementation, training, evaluation and inference
• Writing reports and research papers

Machine Learning Researcher – Audio

• Lead the development of AI use-case solution designs, balancing innovation with practicality.
• Oversee the entire data science / AI delivery lifecycle, from data exploration to model development/tuning to deployment, monitoring, and performance optimisation using ML and AI Ops best practices.
• Lead and work within cross-functional teams comprising of business leaders, product managers, data scientists, data engineers and ML/AI engineers.
• Partner with the Responsible AI team to embed robust ethical principles, bias mitigation techniques, and regulatory compliance into all AI development workflows.
• Coach and mentor junior data scientists and AI engineers, helping to grow team capabilities and fostering a culture of continuous learning and curiosity.
• Maintain an active view of emerging tools and techniques. Develop proof-of-concepts to demonstrate new capabilities. Guide the team in solving complex AI use cases and improving existing approaches.

Lead AI Scientist

• Drive innovation in model serving and inference architectures for advanced AI systems.
• Focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications.
• Work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio.
• Develop, test, and implement novel serving strategies and inference algorithms.
• Engineer robust inference pipelines, establish comprehensive performance metrics, and identify and resolve bottlenecks in production environments.
• Enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios.

AI Research Engineer – Kernel, Inference Optimization

• Architect and maintain knowledge graphs (KG), leveraging ontologies and graph databases.
• Design and implement RAG and GraphRAG pipelines to enhances reasoning for structured, contextual and dynamic data.
• Evaluate and optimize KG, RAG and GraphRAG systems for accuracy, latency and memory trade-off.
• Finetune and deploy various LLMs and adaptors for on-device applications.
• Build robust data generation and collection pipelines for model training and KG, RAG or GraphRAG construction.
• Contribute code libraries by adding new features and improving its capabilities.
• Evaluate the performance of algorithms and systems through rigorous experimentation and statistical analysis.
• Lead the development of software prototypes and experimental systems, ensuring high code quality and maintainability.
• Collaborate with a multidisciplinary team of researchers and engineers to integrate research findings into Samsung products and services.

AI Research Intern – Knowledge Graphs

• Design and develop agentic systems that exhibit autonomous decision-making, goal-setting and task completion
• Design and optimize agentic memory and memory agent frameworks, and multi-agent-interactions
• Finetune and deploy various LLMs and adaptors for on-device and on-server applications using various optimization techniques including reinforcement learning and supervised finetuning
• Contribute code libraries by adding new features and improving its capabilities
• Lead the development of software prototypes and experimental systems, ensuring high code quality and maintainability
• Collaborate with a multidisciplinary team of researchers and engineers to integrate research findings into Samsung products and services.

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Machine Learning Researcher – Audio

Lead AI Scientist

AI Research Engineer – Kernel, Inference Optimization

AI Research Intern – Knowledge Graphs

AI Research Intern