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Synthesia is seeking a Senior Applied Research Engineer to join its Video team and help build the next generation of production-grade foundation models for human-centric video generation. This is applied research with direct product impact—not pure research.
You will own end-to-end research and engineering projects from hypothesis to production, working at the intersection of large-scale generative modeling, distributed systems, and production engineering. Your responsibilities include developing and scaling latent video diffusion models tailored for synthetic human generation, designing conditioning mechanisms to improve control over pose, emotion, script, and camera without sacrificing fidelity, and advancing distributed training strategies (DDP, FSDP, DeepSpeed, sequence parallelism) under real compute constraints.
Key deliverables include improving training stability at multi-node scale, designing rigorous evaluation frameworks combining automated metrics and human evaluation, optimizing inference for low latency and cost efficiency, running controlled ablations to drive modeling decisions, and contributing to high engineering standards around reproducibility, experiment tracking, CI/CD, and monitoring.
You must have strong experience training deep learning models at scale, proficiency in Python and PyTorch, hands-on experience with diffusion models (image domain required; video preferred), and experience with large-scale multi-GPU/multi-node training. Understanding of distributed training frameworks and ability to design controlled experiments are essential.
Nice-to-have skills include video diffusion experience, avatar or human-centric generation background, familiarity with world/interactive models, GAN/VAE experience, and inference optimization for production systems.
The tech stack includes Python, PyTorch, CUDA, DeepSpeed, AWS, SLURM, Docker, and GitHub CI/CD. You'll work in a research-driven but outcome-focused environment where shipping matters more than publishing. Synthesia serves 50,000+ customers including 50% of the Fortune 500, with $4 billion valuation and $530M+ in funding from premier investors including Accel, Nvidia Ventures, and Kleiner Perkins.