小米Machine Learning Engineer-（Experienced）

Engage with others to find opportunities, understand requirements, and translate those requirements into technical solutions Devise machine learning strategies, employing established methods or crafting custom algorithms to address specific business challenges. Communicate analysis findings to non-technical business partners or executives. Research and evaluate new technologies and proven understanding of GenAI concepts and techniques, including RAG, Fine-tuning, RL, Agent, etc. Supervise operational and business metrics, detect adverse trends, recognize behavioral patterns, and respond with agile logic adjustments.

This role requires a blend of skills in software engineering, machine learning, and operations to ensure the smooth functioning of ML systems in production environments. In this role you will: - Lead the team to design and implement automation for model training, testing, validation, and deployment - Collaborate with machine learning engineers to ensure efficient deployment and scaling of ML models - Implement monitoring and alerting systems to track model performance, system health, and data drift - Optimize compute resources for cost and performance efficiency - Manage model versions to ensure traceability and reproducibility

As a member of the AIML team, you will design, implement and ship scalable, reliable and easy-to-use machine learning platform and tools that will be used by Apple product teams. You will also collaborate with teams across Apple, who are building the new, compelling intelligent applications in the world. You bring a strong hands-on mentality that enables you to own engineering projects from inception to shipping product. You will also be a trusted advisor for best practice machine learning development.

THE ROLE: MTS Software development engineer on teams building and optimizing Deep Learning applications and AI frameworks for AMD GPU compute platforms.  Work as part of an AMD development team and open-source community to analyze, develop, test and deploy improvements to make AMD the best platform for machine learning applications. THE PERSON: Strong technical and analytical skills in C++ development in a Linux environment. Ability to work as part of a team, while also being able to work independently, define goals and scope and lead your own development effort. KEY RESPONSIBILITIES: Optimize Deep Learning Frameworks: In depth experience in enhance and optimize frameworks like TensorFlow and PyTorch for AMD GPUs in open-source repositories. Develop GPU Kernels: Create and optimize GPU kernels to maximize performance for specific AI operations. Develop & Optimize Models: Design and optimize deep learning models specifically for AMD GPU performance. Collaborate with GPU Library Teams: Work tightly with internal teams to analyze and improve training and inference performance on AMD GPUs. Collaborate with Open-Source Maintainers: Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream. Work in Distributed Computing Environments: Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems. Utilize Cutting-Edge Compiler Tech: Leverage advanced compiler technologies to improve deep learning performance. Optimize Deep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers. Software Engineering Best Practices: Apply sound engineering principles to ensure robust, maintainable solutions.