Distinguished AI Engineer
Manpower Xem tất cả việc làm
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- Experience in training, fine-tuning, post-training, deploying LLM or foundation models, and integrating them into real-world products.
- Designed training/inference pipelines with multi-GPU, scale-out infrastructure supporting AI in HPC/cloud environments.
- Took on mentor or lead roles in large-scale AI-driven digital transformation projects.
- In-depth knowledge of and application of data standardization, data security, quality testing, and product control for AI in enterprises.Requirements:
- Bachelor's/Master's/PhD in Machine Learning, Artificial Intelligence, Computer Science, Computer Engineering, Information Technology, Data Science, or equivalent.
- Preference given to graduates from prestigious universities ranked in the top 500 QS Ranking or U.S. research universities classified as "R1: Doctoral Universities - Very high research spending and doctorate production" in the Carnegie Classification of Institutions of Higher Education.
- Possess international AI/ML certifications or specialized certifications in Cloud, GPU, distributed systems.
- Preference for candidates who have published AI research papers at conferences/international journals or have participated in AI collaborative research programs.
'- Lead/co-lead AI projects implemented in enterprises, optimizing products to save costs and improve operations.
- Honored with AI technical awards for significant contributions to AI systems or products that integrate LLM and foundation models.
- Published whitepapers, initiatives, or patents recognized internationally; author of multiple open-source tools and modules for the AI development community. Author of at least 2 papers in prestigious conferences, journals, or magazines such as IEEE, ACM, etc.
- Developed and optimized AI pipelines using GPUs, significantly improving training or inference performance compared to previous platforms.
'- Lead/co-lead AI projects implemented in enterprises, optimizing products to save costs and improve operations.
- Honored with AI technical awards for significant contributions to AI systems or products that integrate LLM and foundation models.
- Published whitepapers, initiatives, or patents recognized internationally; author of multiple open-source tools and modules for the AI development community. Author of at least 2 papers in prestigious conferences, journals, or magazines such as IEEE, ACM, etc.
- Developed and optimized AI pipelines using GPUs, significantly improving training or inference performance compared to previous platforms.