Python + Full-Stack Developer

Responsibilities:

Develop and maintain clean, reliable, and scalable software using Python and JavaScript/TypeScript. Build and maintain web applications using modern frontend and backend technologies. Design modular and maintainable software architectures. Develop and review code used in AI model training and evaluation workflows. Evaluate AI-generated responses against defined technical and quality criteria. Create clear explanations and technical reasoning for evaluation results. Support supervised fine-tuning (SFT) by preparing and reviewing high-quality datasets. Contribute to AI evaluation and human-feedback processes. Identify technical issues and recommend improvements to software and AI workflows. Participate in code reviews and provide constructive technical feedback. Write clear, well-organized, tested, and maintainable code. Collaborate with technical teams and other contributors on project requirements. Explore and apply appropriate tools and development practices to improve project outcomes.

Requirements:

Strong programming experience with Python. Strong experience with JavaScript and/or TypeScript. Experience with Node.js or Nest.js. Experience with at least one modern frontend framework: React, Vue.js, Angular Good understanding of JavaScript ES6+ and TypeScript. Experience developing scalable web applications. Understanding of software testing, debugging, and quality assurance. Ability to write readable, reusable, well-documented code. Good understanding of application security and stability. Practical knowledge of Docker is required. Good written and spoken English communication skills. Bachelor's or Master's degree in Computer Science, Engineering, or a related field is preferred; equivalent professional experience may be considered.

Nice-to-Have Skills:

Experience with test-driven development (TDD). Software quality assurance or test planning experience. Previous experience working with large language models (LLMs). Familiarity with AI prompting and AI evaluation workflows. Experience working with AI training, data annotation, SFT, RLHF, or model evaluation.