🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role As a Research Engineer in our Video team, you will help build the next generation of production-grade foundation models for human-centric video generation. You will join a highly focused team working at the intersection of large-scale generative modeling, distributed systems, and production engineering. Our mission is to develop and optimize video base models that power realistic, controllable, and emotionally expressive synthetic humans at scale. This is not pure research. This is applied research with direct product impact. You will work on advancing training recipes, scaling distributed systems, improving evaluation frameworks, and optimizing inference to ensure our models are high quality, stable, and efficient enough for real-world deployment. Your work will directly influence models used by tens of thousands of businesses worldwide. What you’ll do You will own and execute end-to-end research and engineering projects, from hypothesis to production impact. This includes: 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 You will be expected to move fast, run multiple hypotheses in parallel, identify signal early, and focus on outcomes rather than exploration for its own sake. What we’re looking for Must-have 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 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 Our stack Python, PyTorch, CUDA DeepSpeed, distributed training & inference Sequence parallelism AWS, SLURM, Docker GitHub, CI/CD pipelines Who you are You are research-driven but outcome-focused You care about shipping, not just publishing You can explore multiple ideas quickly and drop low-signal directions early You communicate clearly and present results scientifically You operate independently but collaborate actively across teams Why join us? Build production-scale video foundation models in a fast-growing Generative AI company Work on human-centric video generation with real-world impact Tackle hard problems in scaling, stability, and controllability Influence the direction of next-generation synthetic human technology Join a highly technical, high-ownership environment where your work ships If you want to work on cutting-edge generative video models and see your research power real-world products, we’d love to talk. Our culture At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here. Serving 50,000+ customers (and 50% of the Fortune 500) We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2 . Proprietary AI technology Since 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind. AI Safety, Ethics and Security AI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always. Learn more about our commitments to AI Ethics, Safety & Security . The good stuff... 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 You can see more about Who we are and How we work here: https://www.synthesia.io/careers
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.