At a Glance
- Tasks: Join our Video team to create cutting-edge AI video models that impact businesses worldwide.
- Company: Synthesia, a leading AI video platform trusted by top brands.
- Benefits: Competitive salary, stock options, remote work, and 25 days annual leave.
- Other info: Collaborative culture focused on innovation and fast-paced problem-solving.
- Why this job: Make a real-world impact with your research in generative AI technology.
- Qualifications: Strong experience in deep learning, Python, and PyTorch; video diffusion model experience preferred.
The predicted salary is between 80000 - 100000 £ per year.
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.
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.
We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more.
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.
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.
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
Senior Applied Research Engineer - Video Team in London employer: Synthesia
At Synthesia, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Greater London. Our commitment to employee growth is evident through continuous learning opportunities and the chance to work on cutting-edge AI technologies, making every day at Synthesia both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Applied Research Engineer - Video Team in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Synthesia or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Synthesia.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Synthesia.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Synthesia that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior Applied Research Engineer - Video Team in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Synthesia.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Synthesia and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Synthesia
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Synthesia uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
