We are building truly SOTA (State-of-the-Art) video generation foundation models and world models. You will join an elite, lean engineering team spanning across four major areas: B2B/B2C product full-stack development, AI training data platforms, domain-specific big data infrastructure, and frontend engineering. You will be responsible for end-to-end delivery of core business modules-designing, developing, and continuously optimizing our production systems, model training data infrastructure, and cloud architecture to ensure high availability and reliability.
What You Will Do
Microservices Backend: Design and develop core microservices for our video generation platform, covering user management, video task scheduling, billing/credits, payments, API gateways, and content processing pipelines. Maintain sharded high-concurrency MySQL architectures and Kafka asynchronous task streams, ensuring production stability leveraging K8s/EKS and ES/Kibana observability systems.
AI Training Data Platform: Build high-performance data engines for our video foundation model team, managing the full lifecycle of training data processing and dataset version releases. Work closely with the algorithm team to directly drive model iteration efficiency.
Big Data Lakehouse: Build and evolve our big data infrastructure, including data warehousing, Spark offline computing, Trino/Athena interactive querying, and BI dashboards (Superset).
Frontend Engineering: Use React + TypeScript to build and iterate user interfaces across B2B/B2C products, internal data platforms, and operational tools—including data dashboards/visualizations, multi-dimensional filtering and exploration, video previews, human QC interfaces, and task orchestration workbenches.
Ambiguity to Execution: Independently own the end-to-end lifecycle from problem definition - solution design - cross-team alignment - development & deployment - data validation, taking full accountability for delivery outcomes.
What We Expect From You
Basic Qualifications
Bachelor's degree or above in Computer Science, Software Engineering, Telecommunications, or related fields; 3+ years of backend or full-stack software development experience.
Proficient in at least one of the following languages: Java, Python, or Go.
Production Microservices Architecture: Hands-on experience with service decomposition, API design, database sharding, message queues (Kafka / RocketMQ), caching (Redis / Memcached), distributed transactions, idempotency design, and Docker + Kubernetes deployment/ops, backed by a proven track record of building scalable distributed systems.
Frontend Capabilities: Solid engineering skills in React + TypeScript, familiar with state management, build toolchains (Vite / Webpack), component-driven design, and frontend performance optimization (e.g., virtual scrolling for large-scale data tables/lists, video streaming integration). Able to deliver full-stack features independently. Experience with visualization tools like ECharts / AntV is a plus.
Big Data & Data Warehousing: Familiar with Spark, Kafka, CDC sync, data lake tech (at least one of Hudi / Iceberg / Delta Lake), and OLAP engines (Trino / Presto / Athena / ClickHouse, etc.), with experience handling datasets at the hundred-million scale or above.
Cloud Infrastructure: Proficient in at least two major cloud platforms (AWS, Alibaba Cloud, Tencent Cloud) using services such as EKS/ACK, RDS, S3/OSS/COS, MSK, EMR, etc. Multi-cloud or cross-cloud architecture experience is preferred.
Strong Ownership & Problem-Solving: Ability to break down ambiguous requirements without predefined playbooks, deliver high-quality solutions, and proactively validate data correctness rather than settling for code that \"just runs.\"
Preferred Qualifications
AI/ML Engineering Experience: Hands-on experience in ML data pipelines, feature/sample engineering, dataset management, inference serving, or deep involvement in core engineering infrastructure for Large Models (LLMs / Diffusion Models / Video Generation).
Experience in web scraping/data acquisition, copyright compliance, data licensing management, or building data annotation and human audit platforms.
Proficiency with AI coding tools (Cursor, Claude, Copilot, etc.) to significantly boost personal productivity, supported by your own workflows.
Track record of building internal platforms/middle-platforms from scratch (0-to-1), or backend experience with high-concurrency B2C products (1M+ DAU).
Bilingual proficiency: Strong written and verbal communication skills in English (our team is geographically distributed with cross-border collaboration).
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What You Will Do
Microservices Backend: Design and develop core microservices for our video generation platform, covering user management, video task scheduling, billing/credits, payments, API gateways, and content processing pipelines. Maintain sharded high-concurrency MySQL architectures and Kafka asynchronous task streams, ensuring production stability leveraging K8s/EKS and ES/Kibana observability systems.
AI Training Data Platform: Build high-performance data engines for our video foundation model team, managing the full lifecycle of training data processing and dataset version releases. Work closely with the algorithm team to directly drive model iteration efficiency.
Big Data Lakehouse: Build and evolve our big data infrastructure, including data warehousing, Spark offline computing, Trino/Athena interactive querying, and BI dashboards (Superset).
Frontend Engineering: Use React + TypeScript to build and iterate user interfaces across B2B/B2C products, internal data platforms, and operational tools—including data dashboards/visualizations, multi-dimensional filtering and exploration, video previews, human QC interfaces, and task orchestration workbenches.
Ambiguity to Execution: Independently own the end-to-end lifecycle from problem definition - solution design - cross-team alignment - development & deployment - data validation, taking full accountability for delivery outcomes.
What We Expect From You
Basic Qualifications
Bachelor's degree or above in Computer Science, Software Engineering, Telecommunications, or related fields; 3+ years of backend or full-stack software development experience.
Proficient in at least one of the following languages: Java, Python, or Go.
Production Microservices Architecture: Hands-on experience with service decomposition, API design, database sharding, message queues (Kafka / RocketMQ), caching (Redis / Memcached), distributed transactions, idempotency design, and Docker + Kubernetes deployment/ops, backed by a proven track record of building scalable distributed systems.
Frontend Capabilities: Solid engineering skills in React + TypeScript, familiar with state management, build toolchains (Vite / Webpack), component-driven design, and frontend performance optimization (e.g., virtual scrolling for large-scale data tables/lists, video streaming integration). Able to deliver full-stack features independently. Experience with visualization tools like ECharts / AntV is a plus.
Big Data & Data Warehousing: Familiar with Spark, Kafka, CDC sync, data lake tech (at least one of Hudi / Iceberg / Delta Lake), and OLAP engines (Trino / Presto / Athena / ClickHouse, etc.), with experience handling datasets at the hundred-million scale or above.
Cloud Infrastructure: Proficient in at least two major cloud platforms (AWS, Alibaba Cloud, Tencent Cloud) using services such as EKS/ACK, RDS, S3/OSS/COS, MSK, EMR, etc. Multi-cloud or cross-cloud architecture experience is preferred.
Strong Ownership & Problem-Solving: Ability to break down ambiguous requirements without predefined playbooks, deliver high-quality solutions, and proactively validate data correctness rather than settling for code that \"just runs.\"
Preferred Qualifications
AI/ML Engineering Experience: Hands-on experience in ML data pipelines, feature/sample engineering, dataset management, inference serving, or deep involvement in core engineering infrastructure for Large Models (LLMs / Diffusion Models / Video Generation).
Experience in web scraping/data acquisition, copyright compliance, data licensing management, or building data annotation and human audit platforms.
Proficiency with AI coding tools (Cursor, Claude, Copilot, etc.) to significantly boost personal productivity, supported by your own workflows.
Track record of building internal platforms/middle-platforms from scratch (0-to-1), or backend experience with high-concurrency B2C products (1M+ DAU).
Bilingual proficiency: Strong written and verbal communication skills in English (our team is geographically distributed with cross-border collaboration).
Researching careers? Find all the information and tips you need on career advice.
#J-18808-Ljbffr
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