远程岗位： AI 算法工程师（偏 cv）、全栈后端工程师（ Python ）

这两个岗位分别是美国的两家公司招聘，都是 ai 业务，详情可以加 v：emhhbmd5aWp1bjEwMDE=

AI 算法工程师（偏 cv ）
Key Responsibilities:
Develop and Optimize Tagging Algorithms:Lead the design and implementation of robust AI models and algorithms to enhance theaccuracy and relevance of content tagging.
Quality Assurance & Error Resolution:Identify and address issues related to redundant, incorrect, or insufficient tags, ensuring consistent tagging across various media formats.
Innovate for Cost Efficiency:Develop strategies and solutions that optimize processing pipelines, reducing the costs associated with large-scale image and video analysis.
Collaborate Across Teams:Work closely with cross-functional teamsincluding data scientists, engineers, and product managers, to integrate improvements into production systems and drive overall project success.

Required Qualifications:
Education & Experience:
Master’s or PhD in Computer Science, Electrical Engineering, Data Science, or a related field, with a focus on Machine Learning and AI.
5+ years of hands-on experience in machine learning, deep learning, or computer vision,particularly in multimedia content analysis.
Technical Expertise:
Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Background in NLP and computer vision techniques, including image/video processing and semantic tagging.
Experience with clustering algorithms, similarity metrics, and deploying large-scale AI pipelines.
Preferred Qualifications:
Experience developing content tagging systems in digital media environments.
Familiarity with cloud-based AI processing and cost management strategies.
Prior experience in brand marketing or advertising technologies is a plus.


全栈后端工程师（ python ）
## The Role
We're seeking an experienced Backend Engineer to help us scale and enhance our AI agent evaluation platform. You'll work on the core systems that power our leaderboard and evaluation pipeline, from API design to distributed task processing.
## Tech Stack
- Languages & Frameworks: Python (Flask/FastAPI), Javascript/TypeScript (Next.js)
- Databases: PostgreSQL for persistent storage, Redis for caching
- Infrastructure: Docker containers, cloud services (AWS/GCP)
- Tools: Playwright for browser automation, Celery for distributed task queue
## Responsibilities
- API Development: Design and implement RESTful APIs for agent submissions and leaderboard data retrieval
- Evaluation Pipeline: Build and maintain the job orchestration system that runs AI agents against simulated websites
- Security Implementation: Develop secure sandbox environments to safely execute untrusted agent code
- Result Processing: Implement scoring logic and aggregation systems for the leaderboard
- Cloud Integration: Optimize cloud service usage for scalability and cost-efficiency
- Performance Tuning: Monitor and improve system performance across distributed components
## Requirements
- 3+ years of backend development experience, preferably with Python
- Strong knowledge of API design principles and RESTful services
- Experience with asynchronous processing and job queues
- Familiarity with containerization (Docker) and cloud infrastructure
- Understanding of database design and optimization
- Security mindset and knowledge of web application security best practices
## Nice to Have
- Experience with headless browser automation (Playwright/Puppeteer)
- Background in AI/ML systems or evaluation platforms
- Kubernetes experience
- Expertise in distributed systems and scalable architectures