Back to jobsLead end-to-end development of AI systems, including SFT, reward modeling, and RL fine-tuning. Develop reward models and policy optimization frameworks (e.g., PPO, DPO).
Architect reasoning-driven (CoT) and action-oriented (CoA) AI workflows.
Design and implement model training pipelines, evaluation frameworks, and deployment strategies.
Partner directly with customers to understand debug workflows and translate them into AI use cases.
Drive integration of AI systems into engineering platforms.
Establish evaluation metrics, validation methodologies, and risk mitigation strategies.
Mentor junior engineers and interns.
Contribute to long-term AI capability roadmap and technical strategy.Qualifications:
Strong analytical and problem-solving skills.
Proficiency in Python and deep learning frameworks (e.g., PyTorch or TensorFlow).
Familiarity with large language models and modern AI development tools.
Experience with AI orchestration or agent frameworks (e.g., LangChain, AutoGen, etc.).
