Responsibilities
- Develop and improve machine learning and large language model systems for code generation, unit test generation, debugging, and related software engineering tasks.
- Build AI-powered developer agents and workflows that reason over codebases, interact with development tools, execute multi-step tasks, and support the software development lifecycle.
- Improve model and agent performance through prompt engineering, context engineering, retrieval, fine-tuning, reinforcement learning, tool-use design, and agent harness engineering.
- Build training and evaluation data pipelines, including data collection, filtering, synthesis, labeling, and hard-example mining.
- Apply advances in large language models, code intelligence, program analysis, reinforcement learning, and autonomous software engineering to developer productivity problems.
Requirements
- Bachelor’s degree or above in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
- At least 5 years of relevant industry or research experience in machine learning, large language models, code intelligence, AI-powered developer tools, or related areas.
- Strong programming skills in one or more of Python, Go, Java, C++, JavaScript, or TypeScript.
- Understanding of data structures, algorithms, machine learning, operating systems, databases, and fundamental system design principles.
- Experience owning complex machine learning projects end-to-end, including problem formulation, data construction, model development, evaluation, deployment, and production iteration.
- Strong system design and engineering skills, including experience building scalable, reliable, and efficient machine learning systems or AI-powered applications.
- Experience building or leading AI systems for software engineering, such as code generation, coding agents, unit test generation, debugging, or code review, is preferred.
- Deep experience with large language models and model improvement or post-training techniques such as supervised fine-tuning, reinforcement learning, preference optimization, prompt engineering, context engineering, retrieval, or model evaluation is preferred.
- Experience designing agentic systems involving tool-using LLMs, coding agents, agent harnesses, MCP, agent skills, planning, memory, or multi-step execution workflows is preferred.
- Experience building large-scale training data, evaluation datasets, benchmarks, or experimentation pipelines is preferred.
- Understanding of program analysis, compilers, static analysis, code search, repository indexing, testing, and debugging is preferred.
- Publications, patents, open-source contributions, or demonstrated technical leadership are preferred.
- Strong communication and collaboration skills, with the ability to drive complex technical projects across teams.
Tech Stack
Categories
About ByteDance
ByteDance is a global incubator of platforms at the cutting edge of commerce, content, entertainment and enterprise services - over 2.5bn people interact with ByteDance products including TikTok. Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. We are committed to building a safe, healthy and positive online environment for all our users. We have over 110,000 employees based in more than 30 countries globally. Join us.