Senior Research Engineer – Video Foundation Models, Pre-Training

🕒 March 10

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟠 Senior

📚 Research Engineer

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Synthesia

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2017

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

🔥 Funding within the last year

💰 $200M Series E - Synthesia on 2025-10

Artificial Intelligence • SaaS • B2B

<Synthesia> Synthesia is a SaaS AI video platform that enables businesses to create studio-quality videos without cameras, microphones, actors, or studios by using AI avatars and synthetic voiceovers. The platform supports 160+ languages, one-click translation/localization, an AI screen recorder, brand management, collaboration and analytics, and enterprise-grade security (SOC 2 Type II, GDPR). It’s marketed primarily to teams and enterprises for training, sales enablement, marketing, knowledge management and internal communications, helping companies scale video production while reducing time and cost.

📋 Description

• Own and execute end-to-end research and engineering projects, from hypothesis to production impact • Developing and scaling latent video diffusion models tailored for human-centric video generation • Designing conditioning mechanisms to improve control (pose, emotion, script, camera) without sacrificing fidelity • Advancing distributed training strategies (DDP, FSDP, DeepSpeed, sequence parallelism) under real compute constraints • Improving training stability at multi-node scale • Designing rigorous evaluation frameworks combining automated metrics and structured human evaluation • Optimizing inference for low latency, high resolution, and cost efficiency • Running controlled ablations and experiments to drive high-signal modeling decisions • Contributing to high engineering standards: 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 domain required; video preferred) • Experience with large scale multi-GPU / multi-node training • Good understanding of distributed training (DDP, FSDP, DeepSpeed or similar) • Ability to design controlled experiments and interpret noisy results

🏖️ Benefits

• Competitive compensation (salary + stock options + bonus) • Fully remote from Europe or hybrid work setting with an office in London, Amsterdam, Zurich, Munich • 25 days of annual leave + public holidays • Great company culture with the option to join regular planning and socials at our hubs • + other benefits depending on your location