Experience Requirements:

• Solid Python engineering skills: type annotation, exception design, structured logging, code readability and layered design.

• Asynchronous concurrency experience: deep understanding of asyncio (Task, Queue, Event, Lock/Barrier, timeout and cancellation), able to implement highly reliable asynchronous pipelines.

• Event-driven & communication: familiar with pub/sub and RPC (gRPC/WebSocket/Kafka/NATS or one of them).

• Quality and testing: able to write stable tests and mocks for asynchronous logic; experience in CI/CD practices and performance analysis/optimization.

• Low-latency real-time system experience (audio/video/streaming data/command closed-loop or one of them); Decision module development experience (large models, reinforcement learning, rule engines, behavior trees, etc.)

Other Requirements:

• Cross-team collaboration and technical documentation writing skills.

Responsibilities:

• Design/implement asyncio-based action execution pipelines: concurrent scheduling, order guarantee, timeout and cancellation, failure recovery and retry. Establish event-driven mechanisms.

• Interface with external services (such as gRPC/WebSocket/HTTP streaming interfaces), manage connection lifecycle and resources; handle high-frequency state/message streams. Unify serialization/deserialization and protocol constraints, ensuring latency, throughput and stability.

• Develop agent-driven algorithms based on various technologies (large models, reinforcement learning, behavior trees, etc.).

• Based on existing simulation platforms, develop specific atomic actions as required by the project. Generate environment assets through motion capture data or extracting skeletal point data from video streams.

• Improve logging, metrics, tracing, and alerts; build an observable panel for asynchronous links. Establish unit/integration/stress test baselines, locate and solve race conditions, deadlocks and other problems.

Education Requirements:

• Master's degree or above in Computer Science, Artificial Intelligence, Automation or related fields (educational requirements can be relaxed for those with relevant project experience).

Experience Requirements:

• Familiarity with Omniverse platform usage, with relevant development experience for a certain number of years preferred.

• Experience in interdisciplinary learning, work, or research in cognition, vision, reinforcement learning preferred.

Other Requirements:

• Solid programming foundation.

• Good communication skills and teamwork, proactive.

• Strong problem analysis and learning ability, able to quickly follow cutting-edge technologies and apply them to practical problems.

Responsibilities:

• Virtual social scene development (Omniverse), supporting the implementation and verification of various interaction algorithms among multi-agents.

• Social scenes need to support object collision, agent expression and body language display, scene customizability or automatic generation, and customizable agent behavior. Agents in the scene can receive multi-modal signals (e.g., first-person observation images, ambient sound input).

• Responsible for lab Demo development, joint system tackling with other labs and departments, cooperating to implement related systems.

Education Requirements:

• Master's or PhD degree in Computer Science, Mathematics, Statistics or related fields.

Experience Requirements:

• Familiar with Linux system, solid programming skills, data structures and algorithms, proficient in at least two programming languages.

• Familiar with and master principles of various optimization algorithms, machine learning, multi-agent reinforcement learning, deep learning, heterogeneous and asynchronous computing.

• Able to use mainstream frameworks like TF, PyTorch for model building and algorithm tuning.

• (Plus) Published papers in AI journals/conferences.

Other Requirements:

• Strong understanding and knowledge of AI.

• Strong hands-on and fast learning ability, able to quickly follow cutting-edge technologies and apply them to practical problems.

• Good English skills, able to read relevant literature.

• (Plus) Knowledge in complex networks, Bayesian statistics, stochastic processes, information theory, game theory, knowledge graphs.

Responsibilities:

• Participate in cutting-edge research in multi-agent system modeling, agent learning and decision-making, communication and cooperation, game theory, social intelligence.

• Collaborate with team members to complete research projects, read papers, implement algorithms, conduct large-scale experiments.

• Participate in or lead the design and development of platforms or systems, promote the implementation of basic model algorithms.