HeyGen

Software Engineer focused on building and scaling the foundational compute infrastructure for AI models, including multimodal training data pipelines and high-throughput, low-latency video generation. Responsibilities include optimizing GPU utilization, developing large-scale AI job frameworks, enhancing observability, accelerating pipelines with AI researchers, and managing cloud/container technologies.

Tech Lead for AI Compute Infrastructure at HeyGen, focusing on building and scaling the platform for generative video models. Responsibilities include optimizing GPU utilization, developing large-scale AI job frameworks, enhancing observability, accelerating pipelines with custom techniques, and managing cloud/container technologies like Kubernetes and Ray. Requires 5+ years in MLOps/AI infrastructure/HPC, experience with Ray, Spark, Python, C++, Kubernetes, and ML frameworks.

Data Infrastructure Engineer responsible for designing, building, and maintaining data systems and infrastructure to support AI applications, collaborating with data scientists and ML engineers, and optimizing computational workflows. Experience with large-scale AI/ML projects and batch inference systems is required.

This role focuses on improving developer productivity by streamlining engineering workflows, optimizing CI/CD systems, and enhancing build and testing infrastructure. It involves designing and maintaining CI/CD pipelines, developing internal tools, and optimizing build systems. The role requires strong experience with CI/CD tools, build systems, and scripting languages.