You and the process

With a person
Anna, in-house recruiter
9 years hiring engineers
30 minutes with a real recruiter
They read your CV with you, on a call, and say where the offers are being lost.
Didn’t find what you were looking for? Tell us what to build
Be the first to open itNo views yet
Synthesia

Senior Applied Research Engineer - Video

  • Remote
  • 6+ years

Salary

Not stated

AI summary

For members

The whole posting in a few lines. Sign up to read it here and on every role you open.

Sign Up to Read

Description

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 an Applied 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.

Responsibilities

  • 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.

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
  • 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
  • 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

Benefits

  • 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 .

Where you’d work

Fully remote

You can work from

  • Europe
  • United Kingdom

About the company

Synthesia

  • Industry: AI

Also hiring in London, United Kingdom, Seattle, United States, New York City, United States and 4 more places

4 of their 14 open roles are remote

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 19 checks run
  • 2 red flags

Still hiring?

13 checks

1 red flag

How crowded?

6 checks

1 red flag

Fits Me

How well does this role fit you?

Answer a few questions or drop your CV, and every role gets a fit score with the reasons, this one first.

  • Your field
  • Level
  • Stack
  • Work model
  • Salary floor
  • Must-haves
Details12 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • AWS
  • Docker
  • PyTorch
  • LLMs
  • CUDA
Seniority
Senior
Type
Full-time
Industry
AI
Specialty
ML
Region
United Kingdom
Show 6 more factsShow less

Role

Category
Data & Analytics
Specialty
ML
Seniority
Senior
Experience
6+ years
Tech stack
  • Python
  • AWS
  • Docker
  • PyTorch
  • LLMs
  • CUDA

Location

Work model
Remote
Region
United Kingdom
Remote from
  • Europe
  • United Kingdom

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

Company

Industry
AI

Something wrong with this vacancy?

Similar vacancies

  • Early Window: Be the first to open itNo views yetCloses in
    Company hidden

    Data & AI Engineer Intern

    Salary by agreement

    • Hybrid · Paris
    • Junior
  • Early Window: Be the first to open itNo views yetCloses in
    Company hidden

    AI Engineer

    $80,000 - 210,000 / year

    • Office · CA, Austin
    • Senior
  • Early Window: Be the first to open itNo views yetCloses in
    Company hidden

    Senior AI/ML Engineer

    $200,000 - 260,000 / year

    • Office · San Francisco
    • Senior
  • Early Window: Be the first to open itNo views yetCloses in
    Company hidden

    Member of Technical Staff, ML Infra

    Salary by agreement

    • Office · San Francisco
    • Senior

Share this vacancy

What's wrong with it?

The employer never sees who reported.

Reason