FAE (Field Application Engineer) & IT Engineer

Roles & Responsibilities

Responsibilities:

• Requirement Analysis & Solutioning: Engage directly with customers to collect and analyze technical requirements, communicate Ascend AI technical paths, and propose solution plans. Conduct preliminary feasibility and rationality assessments of customer requirements, escalating complex issues promptly while managing satisfaction.
• Environment Deployment: Deploy Ascend AI development and inference environments on single nodes or containers, customizing installations based on product forms and customer model needs. Output comprehensive environment installation and deployment plans, including container image customization for Ascend community releases.
• Development & Usage Support: Resolve technical issues encountered during Ascend development, including API guidance for MindSpore and PyTorch frameworks. Support resource evaluation for model training, assist with model parallelization, and guide offline inference application development using ACL/pyACL or MindX SDK. Provide expertise in ATC model conversion, command-line tools, and integrated development environments like MindStudio.
• Model Adaptation & Migration: Support customers in running and debugging pre-adapted models with operational guidance. For non-adapted models: Guide customers in using migration analysis tools, deploy accuracy/performance collection tools, and assist with full migration and tuning. Execute high-level migration services including research, solution design, implementation, and acceptance, ensuring models land successfully on Ascend.
• Demonstration & Empowerment: Conduct specialized technical sessions using official Ascend samples to address customer-specific pain points. Transfer development skills and explain detailed processes of Ascend AI development, fine-tuning, and inference.
• Issue Management & Escalation: Collaborate with customers to locate and resolve issues arising during model migration, training, and fine-tuning. Identify root causes—whether CANN software bugs, hardware failures, or third-party software issues—and manage appropriate escalation paths.
• Service Scope Governance & Alignment: Ensure all delivery activities remain within the quoted computing power scale and service duration. Upon project entry, align delivery scope with customers through the Technical Director or Project Manager. For out-of-scope requests (e.g., cluster integration, collective communication testing, long-stability training tests), guide customers to Cluster System Integration Professional Services or clarify that third-party/customer delivery applies. Assist Project TDs or Project Managers in monitoring delivery milestones, controlling rhythm, and tracking service order and revenue status to ensure commercial alignment.
• Knowledge Management & Process Improvement: Summarize typical problems, solutions, and case studies encountered during delivery for internal knowledge sharing. Collect, analyze, and systematically feedback customer-side requirements and pain points to product and engineering teams to drive platform evolution.
• To collaborate and communicate directly with China-based Chinese R&D and engineering teams, particularly for roles supporting the Ascend ecosystem.

Requirements:

• Education: Minimum Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Electronic Engineering, or a closely related technical field with distinction.
• Experience: Hands-on experience in AI development and deployment, preferably within cloud computing, semiconductor, or enterprise AI solution environments.
• Professional Background: Knowledge in AI software stack development, model optimization, or system-level performance tuning.
• Programming & Software Development: Proficiency in at least C, C++, or Python (production-grade coding ability required). Experience with Linux-based development, shell scripting, and application debugging (gdb, perf, etc.) is preferred.
• Knowledge: AI & Deep Learning Knowledge of model architectures (Transformers, CNNs, RNNs, ViTs, etc.) and industry trends for CV, NLP, and multimodal models. Solid knowledge of the full AI lifecycle: data pre-processing, training, fine-tuning, validation, inference, and MLOps practices.
• Abilities & Core Competencies (Soft Skills): Ability to listen, empathize, and translate customer pain points into actionable technical solutions; skilled in expectation management and conflict resolution. Good Communication & Presentation, exceptional verbal and written communication skills to articulate complex technical concepts to both technical and non-technical stakeholders. Ability to conduct technical workshops and empowerment sessions.
• Language Proficiency: Proficiency in both English and Mandarin, including speaking, reading, and writing, is required to facilitate effective communication with China-based Chinese R&D and engineering teams, particularly for roles supporting the Ascend ecosystem

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Tell employers what skills you have

Ai
Optimization
Model Driven Development
Generative AI Application Development and Deployment
GNU Debuggers
technical roadmaps
Setup development environment
Computer Proficiency
Deployment Plan
Cloud Deployment
AI Models
PyTorch
technical studies
Customer Requirements Analysis
Parallel Programming
Customer Service Solutions