At a Glance
- Tasks: Train and fine-tune cutting-edge video models to create amazing AI-generated content.
- Company: Join VEED, a leading generative AI company revolutionising video creation for social media.
- Benefits: Enjoy unlimited paid holidays, flexible subsidies, and mental health support.
- Other info: Work remotely or from our hubs in London, Barcelona, or Amsterdam.
- Why this job: Make a real impact in the world of AI video and collaborate with top ML engineers.
- Qualifications: Experience with diffusion or transformer models and strong Python skills.
The predicted salary is between 76000 - 119400 £ per year.
At VEED, we're a generative AI company building the AI video creation platform made for social. It's where millions of marketers imagine and generate branded videos, in minutes. We're powered by frontier models and VEED Fabric, our own image-to-video model. Our APIs also run AI video inside leading creative products. We're 150 people, $50M ARR, backed by Sequoia. We're hiring. Come help us make AI videos worth posting.
Where And How We Work
We’re a distributed team with hubs in London, Barcelona, and Amsterdam. Our ML team is mainly in London, so we’re open to candidates already based there, willing to relocate, or working remotely within 4–5 hours of London time (GMT).
About the team
You’ll be joining a team of experienced ML engineers and researchers (ex-Spiritme, ex-Pipio) working on scaling our generative video models. The team’s goal is to turn breakthroughs in research into fast, reliable, and accessible systems that power VEED’s future.
About the role
We’ve just released Fabric — a DiT-based speech-to-video model that turns spoken words into coherent, human-centric video. We’re now building the next version and a suite of video generation & editing models focused on controllability, quality, and speed. You will work across the full model lifecycle for Fabric 2 and related models — from exploring new research and approaches to training and fine-tuning models. Your work will turn ideas from research into features creators use every day.
What you'll do
- Training and fine-tuning models to create best-in-class generation and editing people-centric video models
- Running experiments to boost visual quality, lip sync, and controllability
- Defining clear metrics and evaluation loops and using them to guide decisions
- Work closely with infra and performance engs and collaborate with the product team
Our Stack
Model/Training: PyTorch, diffusion/DiT, diffusers, transformers, torch.compile, torch.distributed, torchrun, Accelerate, PEFT/LoRA. Serving: Optimised PyTorch/TensorRT runtimes in GPU-backed Python services; experiment tracking, A/B testing, eval pipelines. Hardware: Access to latest-gen NVIDIA GPUs H100 and B200 for training and inference.
About you
- Experience training diffusion or transformer models for video, vision, or audio with results in production or papers
- You care about shipping useful ML, not just benchmarks.
- You enjoy owning problems and collaborating across teams.
- Strong data and experimentation skills and confidence designing practical metrics
- Comfortable writing clean Python and reviewing research with a pragmatic eye
- Clear communicator who can explain trade offs and make sound decisions
- Motivated by impact and by making generative video better, faster, and more accessible
What we offer
- Monthly subsidy programme: Different people have different needs and therefore value different benefits. Providing this as a subsidy allows you to have the greatest flexibility to apply to what you value most - whether that be to offset the cost of office furniture, childcare, gym membership, etc.
- Unlimited paid holidays: We value that you get more time with your family and friends.
- Home office set-up: We have an IT Equipment program to make sure your home office is adequately setup with IT equipment including a laptop, monitors, headsets/earbuds, keyboards and more!
- Mental health benefit: We’ve partnered with Spill to provide all our employees with confidential mental health support.
This role is open at IC3 or IC4 level depending on experience. The salary range across both levels is £76,000 - £119,400 gross per year. The level and offer are determined by the scope of the role and your experience and skills assessed during the process. We do not ask about current or previous salary at any stage. We think what matters is people. After all, a company is just a group of people. We don’t care about where you’re from, what school you went to or where you worked before. If you’ve done exceptional work, we want to hear from you. Join us on our mission to make creative storytelling with video simple and accessible for everyone.
Country Hiring Guidelines: At VEED we are hybrid, enabling teams and individuals to design their day and integrate work and life. We are currently hiring in 3 core hubs: London, Amsterdam and Barcelona and 2 additional hubs for sales and support roles only (USA for sales and the Philippines for support). Please refer to the individual job posts for more details.
ML Engineer employer: Wayfindi
At VEED, we pride ourselves on being an innovative employer that champions creativity and collaboration within our distributed team. With a strong focus on employee well-being, we offer flexible benefits, unlimited paid holidays, and comprehensive mental health support, ensuring that our team members thrive both personally and professionally. Join us in London, where you'll work alongside experienced ML engineers on cutting-edge generative AI projects, all while enjoying a supportive work culture that values your contributions and growth.
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We think this is how you could land ML Engineer
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We think you need these skills to ace ML Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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