Senior Machine Learning Engineer, Developer AI

About the Role
ByteDance’s Dev Infra team is looking for talented Machine Learning Engineers to join our Dev AI initiative. Our mission is to build intelligent systems that transform how engineers design, develop, test, debug, and maintain software at scale.

In this role, you will work at the intersection of machine learning, large language models, code intelligence, and developer infrastructure. You will develop and improve AI systems for code generation, automated testing, debugging, code understanding, and agentic software engineering, with the goal of significantly improving developer productivity across ByteDance.

Responsibilities:
- Develop and improve machine learning and large language model systems for software engineering tasks, including code generation, unit test generation, and debugging.
- Build AI-powered developer agents and intelligent workflows that can reason over large codebases, interact with development environments and tools, execute multi-step engineering tasks, and assist engineers throughout 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 high-quality training and evaluation data pipelines for software engineering tasks, including data collection, filtering, synthesis, labeling, and hard-example mining.
- Explore and apply advances in large language models, code intelligence, program analysis, reinforcement learning, and autonomous software engineering to real-world developer productivity problems at scale.

Minimum Qualifications:
- Bachelor’s degree or above in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
- 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 languages such as Python, Go, Java, C++, JavaScript, or TypeScript.
- Solid understanding of data structures, algorithms, machine learning, operating systems, databases, and fundamental system design principles.
- Experience owning complex machine learning projects end-to-end, from problem formulation and data construction to model development, evaluation, deployment, and production iteration.
- Strong system design and engineering skills, with experience building scalable, reliable, and efficient machine learning systems or AI-powered applications.
- Strong communication and collaboration skills, with the ability to drive complex technical projects across teams.

Preferred Qualifications:
- Experience building or leading AI systems for software engineering, including code generation, coding agents, unit test generation, debugging, or code review.
- Deep experience with large language models and one or more model improvement or post-training techniques, such as supervised fine-tuning, reinforcement learning, preference optimization, prompt engineering, context engineering, retrieval, or model evaluation.
- Experience designing and improving agentic systems, including tool-using LLMs, coding agents, agent harnesses, MCP, agent skills, planning, memory, or multi-step execution workflows.
- Experience building large-scale training data, evaluation datasets, benchmarks, or experimentation pipelines for machine learning or code intelligence systems.
- Strong understanding of software engineering and code intelligence techniques such as program analysis, compilers, static analysis, code search, repository indexing, testing, and debugging.
- Publications, patents, open-source contributions, or demonstrated technical leadership in machine learning, large language models, code intelligence, developer tools, or AI for software engineering.