Member of Technical Staff, AI
We are seeking highly technical and product-minded Member of Technical Staff (AI Algorithms & Systems) to build core intelligence for automating the software development lifecycle. This opportunity requires a strong intuition for LLMs, applied research ability, and a bias toward shipping.
Key Responsibilities
LLM Systems & Applications
Design and develop LLM-powered systems for code understanding, generation, and reasoning.
Build agents and workflows that automate complex parts of the software development lifecycle.
Improve reliability, accuracy, and controllability of AI behaviors in production.
Algorithm & Model Development
Research, implement, and refine algorithms for reasoning, retrieval, planning, and tool use.
Develop advanced prompting, RAG, and agentic architectures.
Contribute to fine-tuning, distillation, and specialized model work when needed.
Evaluation & Optimization
Build evaluation frameworks to measure model quality, performance, and reliability.
Run experiments to identify areas for model and system improvement.
Optimize AI pipelines for latency, cost, and scalability.
Integration
Work cross-functionally with infrastructure, product, and engineering teams to ship AI capabilities end-to-end.
Integrate AI features into developer tools, IDEs, CI/CD systems, and internal platforms.
Research to Production
Translate state-of-the-art research into practical, production-ready systems.
Stay ahead of advancements in LLMs, agentic AI, and AI-assisted software engineering.
Qualifications
Strong background in machine learning, NLP, or applied AI research.
Experience building with LLMs and modern AI tooling (LangChain, LlamaIndex, OpenAI, Anthropic, etc.).
Proficiency in Python and familiarity with ML frameworks (PyTorch, Hugging Face).
Experience shipping end-to-end AI systems in real products.
Strong problem-solving and experimental mindset.
Ability to operate independently in ambiguous, fast-moving environments.
What We Value
Preference for simple, scalable solutions.
Fast iteration loops and a bias toward action.
Ability to bridge research and production.
Deep curiosity about AI and its applications in software engineering.