AI Amplify Researcher

The Metabit Amplify Team is an elite squad dedicated to building AI-native engineering infrastructure. We design and implement end-to-end AI coding agent systems that multiply every engineer's productivity by 3-5x.
We don't write trading strategies—we build tools and systems that multiply strategy engineers' efficiency. We are also firm believers and practitioners of open source:
Embracing Open Source: We stand on the shoulders of giants, actively adopting and integrating cutting-edge open source technologies to stay in sync with the global AI community.
Contributing Back: We don't believe in building in isolation. As we refine our systems, we will progressively open source this secure, reliable, and efficient AI-native engineering infrastructure.
Responsibility
Research LLM-based coding agents, including key capabilities such as planning, tool use, memory, and long-horizon reasoning
Explore how AI understands and operates on real-world large codebases and development toolchains
Design new agent architectures and algorithms to push the boundaries of AI-automated software development
Build evaluation frameworks and benchmarks to measure coding agent capabilities in bug fixing, feature implementation, code migration, and test generation
Rapidly prototype research ideas and validate them in real engineering environments
Analyze the capabilities and limitations of frontier models (Claude, GPT, Codex, etc.)
Track and reproduce latest research results from OpenAI, Anthropic, DeepMind, and the open source community
Collaborate with engineering teams to transform research outcomes into production systems
Participate in the broader research community through open source, technical reports, or papers
We expect you to:
Strong foundation in computer science (algorithms, systems, machine learning, etc.)
Strong interest in LLMs, Agent Systems, and AI Coding
Project experience with LLMs or AI agents
Ability to design experiments and systematically evaluate AI system capabilities
Excellent programming skills (Python preferred)
Ability to quickly understand papers and new technologies and implement prototypes
Self-driven with a passion for exploring open-ended problems
Bonus points:
Research experience in LLMs, code models, program synthesis, or automated debugging
Publications or technical talks in ML / Systems / Software Engineering
Familiarity with large codebases or developer infrastructure
Contributions to open source AI projects
Experience with AI coding tools (Copilot, Claude Code, SWE-agent, Devin, etc.)