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亚马逊Sr. AI Process Engineer, Seller Compliance

社招全职Sales Operations Job Family地点:上海状态:招聘

任职要求


基本任职资格
- Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, or similar).
- Demonstrated experience designing, implementing, and operating production AI systems at scale.
- Hands‑on experience with cloud platforms (preferably AWS) and associated ML services.

优先任职资格
- Master’s degree in Computer Science, Machine Learning, or a related field.
- Experience with NLP, deep learning, or document understanding applications.
- Experience working with Compliance, risk management, or other highly regulated systems.
- Proven track record of leading technical teams or initiatives and mentoring engineers.
- Hand…
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工作职责


Technical Development & Architecture
* Design and implement scalable AI/ML solutions for Compliance use cases 
* Lead the development of efficient ML models and end‑to‑end data processing pipelines from ingestion to serving.
* Build robust, production-grade AI services using Python and modern ML frameworks.
* Make and document sound architectural decisions, ensuring systems are scalable, secure, and cost‑effective.
* Establish and maintain high engineering standards, including testing, monitoring, and documentation.

Engineering Leadership
* Partner closely with data scientists, product managers, and operations teams to deliver end‑to‑end AI/ML solutions.
* Define and evolve the technical architecture for AI-powered features and platforms.
* Lead code reviews, enforce best practices, and elevate engineering quality across the team.
* Continuously improve AI system performance, reliability, and latency through experimentation and optimization.

Technical Collaboration & Operations
* Work with cross‑functional partners to understand requirements, refine scope, and prioritize technical work.
* Provide technical guidance and mentorship to junior and mid‑level engineers.
* Collaborate with platform and DevOps teams to ensure smooth deployment, monitoring, and maintenance of AI systems.
* Implement and evolve ML Ops practices (e.g., CI/CD for models, feature stores, model monitoring, and retraining workflows).
包括英文材料
Python+
PyTorch+
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