Chief AI Scientist

6 days ago

Singapore Robert Walters Full time

Position Summary As the Chief AI Scientist, you will spearhead the development and deployment of cutting‐edge AI technologies, particularly in LLM and NLP domains. Reporting directly to the CTO/CEO, you will drive strategic AI research, foster innovation, and collaborate with cross‐functional teams to integrate AI solutions that enhance our products and services. This role demands a blend of technical expertise, leadership, and a passion for pushing the boundaries of AI. Key Responsibilities Lead the AI research and development team, setting the vision and roadmap for LLM and NLP projects, including model training, fine‐tuning, and optimization. Design and implement advanced LLM architectures (e.g., based on transformers like GPT, BERT, or similar) for applications such as natural language understanding, generation, sentiment analysis, and conversational AI. Oversee NLP initiatives, including text processing, entity recognition, machine translation, and semantic analysis, ensuring scalability and ethical AI practices. Collaborate with engineering, product, and data teams to deploy AI models into production, focusing on performance metrics like accuracy, latency, and resource efficiency. Mentor junior scientists and engineers, fostering a culture of innovation and continuous learning. Evaluate and integrate emerging AI tools, frameworks, and datasets to accelerate development. Ensure compliance with AI ethics, bias mitigation, data privacy regulations (e.g., GDPR), and responsible AI deployment. Partner with external stakeholders, including academia and industry leaders, to drive collaborative AI projects. Required Qualifications PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field; or equivalent professional experience. 10+ years of experience in AI research and development, with at least 5 years in leadership roles focused on LLM and NLP. Proven track record of developing and deploying production‐grade LLM/NLP models, demonstrated through publications, patents, or successful projects. Deep expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers) and NLP libraries (e.g., spaCy, NLTK). Strong understanding of deep learning architectures, including attention mechanisms, reinforcement learning from human feedback (RLHF), and multimodal integration. Experience with large‐scale data handling, cloud computing (e.g., AWS, GCP), and distributed training systems. Excellent leadership and communication skills, with the ability to translate complex technical concepts to non‐technical stakeholders. Do note that we will only be in touch if your application is shortlisted. #J-18808-Ljbffr

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