Applied Algorithms Researcher
Seeking an Applied Algorithms Researcher for groundbreaking work in AI code generation at the forefront of GPT-4 technology. Ideal candidates are pioneers in AI with academic and applied research backgrounds, ready to innovate in code generation, evaluation flows, and multi-agent architectures.
About the Role
Codegen seeks an Applied Algorithms Researcher to push the boundaries of what GPT-4 and subsequent models can achieve, focusing on the core research machine and algorithms for code generation. This includes evaluation flows, multi-agent architectures, and code modification methodologies. The ideal candidate possesses a blend of academic research experience in AI from the pre-LLM era, hands-on software engineering outside academia, and a specific research interest in code generation and multi-agent systems. We value individuals who are prolific in developing research code to production quality and capable of self-guided research. This role is perfect for someone passionate about the rapid progress in AI, who prefers the dynamism of a cutting-edge research environment over traditional academia.
Our technology ecosystem is Python-centric, employing OpenAPI APIs, FastAPI, and Modal for backend development. We emphasize deep git integration, use Retool for internal applications, and maintain a minimal frontend using Remix.js and TypeScript.
Qualifications
Academic research experience in AI, preferably before the large language model (LLM) era, demonstrating a deep curiosity about AI.
Software engineering experience outside the university, ideally in applied research settings like Google, DeepMind, Anthropic, etc.
Focused research interest in code generation and multi-agent systems.
Proven ability to develop research code and elevate it to production quality.
Self-guided research capabilities.
A strong desire to contribute to fast-paced AI advancements outside of academia.
Responsibilities
The selected candidates will be tasked with:
Expanding our AI capabilities, including setting up evaluation flows, developing core algorithms for knowledge management and updates, and establishing the core architecture for generating AI-driven solutions.
Prototyping new solutions and collaborating with the engineering team to transition these into production.
Engaging in significant exploratory data analysis and working closely with senior software engineers to implement sophisticated algorithms.
Average salary estimate
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