Currently tracking 6 active AI roles, down 17% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $175k–$225k (avg $200k).
HeyGen currently has 9 active AI-related job listings. The company's hiring is concentrated in application and serving infrastructure roles, each representing 33% of the active listings. Engineering is the dominant function, with 7 positions. The majority of these roles are located in the United States. HeyGen is actively seeking candidates with experience in model serving, inference infrastructure, and multimodal technologies.
HeyGen currently has 7 active AI-related roles in our index. The most common open titles are: Data Infrastructure Engineer, Fullstack Software Engineer, Head of Developer Experience, Research Engineer, Software Engineer, AI Compute Infrastructure. Most positions are in Engineering and Research.
HeyGen's active AI hiring is concentrated in: serving infrastructure (43%), application (29%), post-training (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
HeyGen is hiring AI talent in: United States (7 roles), Canada (3 roles).
Job postings at HeyGen most frequently reference: model serving, inference infra, multimodal, agent orchestration, vision.
| Title | Stage | AI score |
|---|---|---|
| Software Engineer, AI Compute Infrastructure 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. | ServeData | 8 |
| Tech Lead, AI Compute Infrastructure 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. | ServeData | 8 |
| Data Infrastructure Engineer 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. | Serve | 7 |