Full-stack Software Engineer for AI Platform and App Operation
4 weeks ago
Leading open source library in large-scale distributed training, model serving, and federated learning (FedML)
Innovative and unique edge-cloud collaborative AI models and systems towards on-device personal AI (Fox LLM)
Internet veterans for serving billion-level end users based on cloud computing and mobile internet
Established researchers in blockchain, machine learning, and large-scale distributed systems (80000+ citations)
Ecosystem partnership with GPU providers, model developers, AI platforms, and AI applications
Top-tier investors, angels, and advisors
Responsibilities:Design, develop, and maintain both front-end and back-end components of our AI platform and applications
Collaborate with AI researchers and data scientists to implement machine learning models into production systems
Optimize application performance and scalability to handle large-scale AI operations
Implement robust security measures to protect sensitive data and ensure compliance with industry standards
Participate in the full software development lifecycle, from conception to deployment and maintenance
Write clean, efficient, and well-documented code
Troubleshoot, debug, and upgrade existing software
Requirements:Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
5+ years of experience in full-stack software development
Proficiency in front-end technologies such as React, Angular, or Vue.js
Strong back-end development skills using languages like Python, Java, or Node.js
Experience with database systems (SQL and NoSQL)
Familiarity with cloud platforms (AWS, Google Cloud, or Azure)
Understanding of AI and machine learning concepts
Experience with RESTful APIs and microservices architecture
Knowledge of version control systems (e.g., Git)
Preferred Qualifications:Experience with blockchain technologies and smart contract development
Familiarity with AI frameworks such as TensorFlow or PyTorch
Knowledge of DevOps practices and tools
Experience with containerization technologies (e.g., Docker, Kubernetes)
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