Senior Applied Research Engineer - Video

Stack

Responsibilities

• ▹Develop and scale latent video diffusion models
• ▹Design conditioning mechanisms (pose, emotion, script, camera)
• ▹Advance distributed training strategies (DDP, FSDP, DeepSpeed)
• ▹Improve training stability at multi-node scale
• ▹Design evaluation frameworks with automated and human metrics
• ▹Optimize inference for low latency and cost efficiency
• ▹Run controlled ablations and experiments
• ▹Ensure reproducibility, experiment tracking, CI/CD, monitoring

Requirements

• ▹Strong experience training deep learning models at scale
• ▹Strong Python and PyTorch skills
• ▹Hands-on experience with diffusion models (image required, video preferred)
• ▹Large-scale multi-GPU / multi-node training experience
• ▹Good understanding of distributed training (DDP, FSDP, DeepSpeed or similar)
• ▹Ability to design controlled experiments and interpret noisy results

Nice to have

• ▹Experience with video diffusion models
• ▹Experience in avatar or human-centric generation
• ▹Familiarity with world/interactive models
• ▹Experience with GANs or VAEs
• ▹Experience optimizing inference systems for production

Soft skills

About the company

Synthesia is the world's leading enterprise AI video platform, used by over 90% of the Fortune 100; it recently raised $200M in a Series E round at a $4B valuation.