HeyGen

This role involves deploying and integrating AI video platform solutions for enterprise customers, acting as a bridge between customer needs and HeyGen's product/engineering teams. It requires owning end-to-end deployments, building on the HeyGen API, managing escalations, and providing feedback to product development. The role emphasizes customer-facing AI systems and requires hands-on experience with generative AI in production.

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.

Research Engineer focused on applied innovation in generative models (GANs, Diffusion) and computer vision for video creation tools, translating research into scalable, user-facing features. Requires Master's/PhD and 1-3 years of ML/CV experience with deep learning frameworks.

Software Engineer with data engineering responsibilities to build data foundational layers for next-generation features, enabling AI models to function in real-time and powering engaging user experiences. The role involves building and scaling data pipelines for multimedia data, powering intelligent features, architecting data lakehouse solutions, ensuring data reliability, and productizing data for AI agents.

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.