At a Glance
- Tasks: Build and enhance backend systems for our innovative dubbing product using cutting-edge AI technology.
- Company: Join Synthesia, a leading AI video platform trusted by top brands worldwide.
- Benefits: Enjoy a competitive salary, stock options, and 25 days of leave plus local holidays.
- Other info: Remote role with excellent career growth opportunities in a dynamic environment.
- Why this job: Be part of the AI revolution and make a real impact in video localization.
- Qualifications: Strong backend engineering skills and experience with long-running workflow systems.
The predicted salary is between 130000 - 130000 £ 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.
About the role: You will work on the engineering systems powering Synthesia's dubbing product, the multi-step pipeline that transforms existing videos into new-language versions while preserving lip sync, voice quality, timing, and overall video integrity. Your role centers on the core challenge: building a production system that orchestrates complex, long-running jobs (often taking tens of minutes to hours) with reliability, observability, and quality at every stage. You'll ensure that localized videos are indistinguishable from originals, working across transcription, speaker identification, translation, voice synthesis, and video rendering.
You will be responsible for designing and evolving systems that handle:
- End-to-end pipeline orchestration for long-running, multi-stage jobs
- Quality layers across transcription accuracy, speaker diarization, lip-sync rendering, translation, voice cloning, and TTS
- Integration of ML-driven components (providers and open-source models) into production workflows
- Video and audio complexity (normalization, chunking, encoding, vocal separation, retiming)
- Evaluation frameworks that prove measurable improvements in output quality
You will own projects that span multiple systems and domains, such as:
- Building robustness layers (retries, idempotency, failure recovery) for long-running pipelines
- Designing persistence and state management to ensure consistent voice outputs across regenerations
- Improving how video and audio data is processed, cached, and reused
- Integrating new transcription, translation, voice synthesis, and video rendering providers
- Building evaluation harnesses around each pipeline stage to measure quality reliably
You will evaluate your work through system performance, user experience metrics, and observability, using tracing and debugging tools to identify bottlenecks and continuously improve reliability. You will collaborate closely with product, frontend, and ML/R&D teams, ensuring backend systems support both current product needs and future innovation in video localization.
What we're looking for:
Must-haves:
- Strong production backend engineering fundamentals (design, reliability, performance, maintainability)
- Experience building and operating async, batch, or long-running workflow systems (jobs, retries, failure modes, observability)
- Comfort operating in ambiguity and making trade-off decisions (quality vs cost vs speed)
- Enough ML literacy to integrate, evaluate, and iterate on models and third-party providers (not necessarily an MLE)
- A product mindset focused on solving user-facing problems from a backend perspective
Nice-to-haves:
- Video, audio, or media pipeline experience (codec, fps, ffmpeg-like realities)
- Shipped systems that integrate ML outputs into product-facing workflows
- Built evaluation frameworks for quality (both offline testing and production monitoring)
- Experience with observability tools (e.g., Datadog), workflow systems (e.g., Temporal), or recommendation/evaluation systems
- Willingness to step outside your comfort zone—including jumping into frontend code to debug end-to-end flows
Why join us? We’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one.
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.
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.
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.
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.
The hiring process:
- 30-40min call with our Technical Recruiter
- 45min call with an Engineering Manager about your past projects
- 90min Live Coding interview, a collaboration exercise with our Engineer (not Leetcode style)
- 60min System Design, technical discussion usually about a real problem we had in production
- 45min call with leadership, focus on examples of collaboration, growth and going through details of your future team
The process does not need to take long - we can be done in seven working days.
This is a remote role from an EU country, UK or Switzerland. The salary starts at EUR/GBP/CHF 130,000 base + stock option plan. This is full-time employment only - no contractors possible - usually through OysterHR. Everyone at Synthesia gets 25 days of leave + local holidays (no extra paid or unpaid leave possible). We only sponsor VISA if you are in the UK/EU country already and need support.
Staff Backend Engineer, Dubbing in London employer: Synthesia
At Synthesia, we pride ourselves on fostering a dynamic and innovative work culture that empowers our employees to excel in their roles. As a leading AI video platform, we offer competitive salaries, generous stock options, and 25 days of leave, ensuring a healthy work-life balance. Our commitment to employee growth is evident through collaborative projects and a focus on cutting-edge technology, making us an exceptional employer for those looking to make a meaningful impact in the AI industry.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Backend Engineer, Dubbing in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Prepare for those interviews! Research Synthesia and its products, especially the dubbing tech. Show us you’re not just another candidate but someone who’s genuinely excited about what we do.
✨Tip Number 3
Practice coding live! We want to see how you think and solve problems in real-time. Grab a friend or use online platforms to simulate that pressure.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our team!
We think you need these skills to ace Staff Backend Engineer, Dubbing in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Staff Backend Engineer role. Highlight your experience with backend systems, especially those involving long-running workflows and ML integration. We want to see how your skills align with what we do at Synthesia!
Showcase Your Projects:When detailing your past projects, focus on those that demonstrate your ability to build reliable and maintainable systems. We love seeing real-world examples of how you've tackled challenges similar to what you'll face here, so don’t hold back!
Be Clear and Concise:Keep your application clear and to the point. Use straightforward language to describe your experiences and achievements. We appreciate clarity, and it helps us understand your background better without sifting through fluff.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our team at Synthesia!
How to prepare for a job interview at Synthesia
✨Know Your Tech Inside Out
Make sure you’re well-versed in backend engineering fundamentals, especially around async and long-running workflows. Brush up on your knowledge of ML integration and be ready to discuss how you've tackled similar challenges in the past.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your product mindset. Think about how you've solved user-facing problems from a backend perspective, particularly in relation to video and audio processing. Be ready to discuss trade-offs you've made between quality, cost, and speed.
✨Familiarise Yourself with Their Tools
Get to know the observability tools and workflow systems mentioned in the job description, like Datadog and Temporal. If you have experience with these or similar tools, be sure to mention it during your interview.
✨Prepare for Collaborative Discussions
Since collaboration is key at Synthesia, think about times when you've worked closely with cross-functional teams. Be prepared to share how you’ve communicated effectively with product, frontend, and ML teams to ensure backend systems meet their needs.