On a daily basis, you will
- Develop and maintain Python-based tooling and infrastructure to support AI-driven solutions for code quality and security.
- Implement and optimize AI-focused experiments, creating robust systems to evaluate modern techniques, including fine-tuning, retrieval-augmented generation (RAG), direct preference optimization (DPO), and reinforcement learning from human feedback (RLHF).
- Write scalable, production-quality Python code to support AI workflows, dataset processing, and evaluation frameworks.
- Design and maintain benchmarking pipelines to assess Large Language Model (LLM) performance in generating clean, maintainable code.
- Process and refine datasets, ensuring they’re structured and optimized for training and evaluation.
- Develop integrations between AI systems and static analysis tools, enabling AI-assisted insights for developers.
- Collaborate with static analysis experts and AI researchers to turn experimental ideas into practical, working solutions.
- Ensure the scalability, reliability, and maintainability of AI tooling as it transitions from experimentation to production.
- Continuously improve the development processes via workflow refinement, automation, and tooling for AI-assisted coding.
- Work in a fast-paced, iterative environment that bridges research-driven innovation with real-world software development.
The Skills You Will Demonstrate
- Proven expertise in Python development, writing clean, maintainable, and efficient code.
- Solid software engineering foundation, including algorithms, testing, CI/CD, and best practices for building scalable and reliable software.
- Deep curiosity about LLMs, static analysis, and multiple programming languages, recognizing their strengths, challenges, and nuances.
- Genuine interest in AI-driven software development, and a willingness to work on projects integrating AI with developer tools.
- Pragmatic approach to problem-solving, balancing research-driven innovation with building production-ready systems.
- Self-driven mindset, bold enough to challenge the status quo, yet humble and open to learning and feedback.
- Bonus points for hands-on experience with LLM-related projects, static analysis, or proficiency in additional programming languages (e.g., TypeScript, Java, C#).
Required Soft Skills
- Initiative and Ownership: You can take a task from concept to completion with minimal supervision.
- Curiosity and Adaptability: You thrive in a fast-moving environment, staying eager to learn new technologies and experiment with AI-driven solutions.
- Open-mindedness and a Positive Attitude: You welcome new ideas, embrace feedback, and collaborate effectively with diverse teams.
- Comfort with Complexity and Change: You excel at navigating uncertainty, iterating quickly, and adjusting to evolving challenges.
- Confidence to Challenge and Be Challenged: You’re unafraid to question assumptions and engage in constructive discussions to drive the best outcomes.
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