Reinvent speech recognition technologies to empower us collectively.
AI is an incredible thing, especially when we put it to the service of humanity — and not the other way around. We love hearing incredible applications of computer vision, from detecting cancer by looking at your eye or saving your life by making driving autonomous & more secure. But speech recognition applications? They've stayed pretty much at the gadget level, inundating us with talking alarms and smart home assistants.
Ava is the exception to the rule - the ampersand-shaped peg in a rather boringly square world. We reinvent speech recognition and speaker identification technologies so we can help 450M deaf & hard-of-hearing people live a fully accessible life. With Ava, they can understand what everyone else is saying in any group conversation, anytime.
A difficult challenge to solve? Yes, and that's what we love. What really keeps us up at night though, is the thrill to be impacting day to day people in a meaningful way. And see the smile on our users' faces when they use our product.
Don't waste more of your precious gray matter in politics-laden research teams in big companies, and come instead shine your light where the world can see the impact of what you do!
What will you do as a Machine Learning Scientist at Ava?
- You'll own one of the Ava's AI team research objectives to develop solutions for real-world applications of our core technology.
- You'll keep an eye out on the state-of-the-art research, through publications or networking with peers, and think of new contributions to improve the state of our stack.
- You'll help improve the performance and reliability of our cutting-edge AI systems — such as improving the speed and responsiveness of our deep neural networks.
- You'll work with the rest of the AI team to build and maintain robust internal machine-learning tools and processes, with a focus on our Machine Learning models. Think of projects such as detecting new voices in a 0-shot learning setting, separating overlapped speech or cleaning speech from strong background noises.
You'd be perfect for this role if:
- You ambition to be a pioneer in the field, and do what is necessary to make things work in real world situations.
- You have a PhD degree in machine learning, signal processing or related area.
- You have 3+ years of research experience in machine learning (esp. deep learning).
- You have experience in speech or audio processing.
- You're of the persistent, yet open-minded and collaborative type: you can own and pursue a research agenda and autonomously carry it out, but appreciate working .
- You care about the strategic and business implications of anything you build. You're not just going after cool stuff — you understand the balance between craft, speed, and the bottom line.
- Bonus: You have experience in speaker diarization, speaker identification, speech recognition, acoustic modeling, language modeling or source separation.
- Bonus: You have past experience creating high-performance implementations of deep learning algorithms.
What's special about this role?
- Actually change lives at an unprecedented scale: How often do you hear about apps that make people cry of joy? It is really for us a unique opportunity and privilege to be able to meaningfully improve the lives of 100,000s of people - and yet to still be at the very beginning of our mission!
- Work with some of the best people in the world: We have an incredibly talented and passionate team that is a lot of fun to work with. We're still small and have accomplished some things that were thought impossible!
- Tackle our most interesting and impactful problems: Our AI team is growing very fast. You'd jump between machine-learning models, speech processing algorithms, internal tools, process — participating in every phase from inception to implementation. Absolutely no boredom.
- Join us at an incredible time: We're well-funded Series A company and hit product-market fit, which gives us a huge green field to work with. You'd join at the perfect time to shape what we build and how we grow, so we can create a more inclusive world.