We’re on a mission to make the world's videos watchable in any language
Papercup uses AI to dub videos into other languages using the most human sounding synthetic voices you've ever heard.
Leaders in entertainment, news, and enterprise, such as Jamie Oliver, Business Insider and Bloomberg, use Papercup every day to leap language barriers and engage more deeply with their international audiences. Last year alone over 900 million people watched videos translated by Papercup. But this is just the start - billions of hours of video are stuck in a single language - our technology will fundamentally change that and make videos watchable in any language.
We’re more than just an AI startup - we also care deeply about our people. We want people to feel fulfilled, rewarded and genuinely happy at Papercup. That’s why creating and fostering the right culture matters to us and why we’re committed to building a company that people are proud to work for.
If you want to work on a game changing technology and you care about working with a fun, smart and humble team, we’d love to hear from you.
What you'll do with us:
As a Machine Learning Engineer at Papercup, you will be part of a great team pushing the boundaries of neural text-to-speech and speech-to-speech translation systems.
You will own and push forward your projects during the whole research cycle, writing code implementation, running experiments, evaluating results, drawing conclusions. You will also contribute to maturing our research prototypes into fully-fledged production models as well as deploying them in our cloud infrastructure.
We are looking for strong engineers and research scientists who have a background in generative AI and NLP, with experience in areas like language model evaluation; data processing for pre-training and fine-tuning, reinforcement learning for language model tuning, efficient training and inference; and/or multilingual and multimodal modeling
- Design methods, tools, and infrastructure to push forward the state of the art in large language models applied to speech and audio
- Define research goals informed by practical engineering concerns.
- Contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organising results.
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
What we are looking for from you:
- You have practical experience training state-of-the-art LLM models
- You have at least a bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- You have extensive and hands-on programming experience in Python and frameworks such as PyTorch
- Research experience in machine learning, deep learning, and/or natural language processing with first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).
- Proven strong product mindset, with a focus on building the best experience for the end-user
Why you should consider us?
- We really care about our people - culture matters deeply to us and we are committed to building a company that people are proud to work for
- We're growing fast. That means you can help grow the business from the ground up and maintain a lot of ownership
Apart from all this good stuff, what else do we offer?
- Competitive salary and options
- Unlimited vacation policy
- Hybrid working: flex between WFH and time in our Aldgate office (2 days per week)
- Private medical cover or monthly wellness bonus
- Learning budget and 'reading week' to carve out time to up-skill in your domain
- The usual food and fun perks: snacks, beer fridge, regular team socials, annual offsites
The FlexScore® is the result of a rigorous 2-step verification of a company’s flexibility
First we assess the flexibility options Papercup provides and then we anonymously survey a statistically significant proportion of their employees to make sure Papercup is as flexible as they say they are. Our assessment is based on the six key elements of flexibility: location, hours, autonomy, benefits, role modelling and work-life balance.
We ask the hard questions so you don’t have to.
Working at Papercup
Gender diversity (male:female)
London - Aldgate
$20m Series A