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Machine Learning Engineer
2 months ago
We are seeking a highly skilled Machine Learning Engineer to join our team at Hireio, Inc. as a key member of our technology team. The successful candidate will be responsible for developing and optimizing large-scale language models to drive business growth and innovation.
Key Responsibilities- Large Scale Model Development: Design, develop, and deploy large-scale language models to meet business requirements, leveraging expertise in machine learning, natural language processing, and software engineering.
- Model Optimization: Continuously optimize and refine models to improve performance, efficiency, and scalability, ensuring seamless integration with existing systems.
- Collaboration and Innovation: Work closely with cross-functional teams to identify new opportunities for model application, driving innovation and business growth through data-driven insights.
- Research and Development: Stay up-to-date with the latest advancements in machine learning and natural language processing, exploring new techniques and technologies to enhance model performance and capabilities.
- Technical Expertise: Proven expertise in machine learning, natural language processing, and software engineering, with a strong foundation in data structures, algorithms, and programming languages (C/C++ or Python).
- Industry Experience: Experience in one or more areas, including NLP, ranking, ads, search engines, recommender systems, distributed systems, and machine learning.
- Algorithmic Knowledge: Familiarity with NLP-related algorithms, technologies, and large-scale model training, with a strong understanding of reinforcement learning algorithms.
- Problem-Solving Skills: Excellent problem analysis and solving skills, with the ability to deeply solve complex problems in large-scale model training and application.
- Communication Skills: Good communication and collaboration skills, with the ability to effectively communicate technical ideas and drive technological progress.
Fluency in Mandarin is preferred, but not required.