Nota AI GmbH - Berlin
We are a fast-growing tech startup that focuses on AI model optimization, and we created the leading platform solution called NetsPresso. We offer a diverse range of edge AI solutions, including on-device intelligent transportation systems, facial recognition-based access control, and low-powered driver monitoring solutions for vehicles.
Nota is headquartered in Seoul, South Korea, and we opened our first subsidiary in Berlin in 2020 with currently 7employees here.
We have acquired a series B funding amounting to USD 14.7M in November 2022, a year after the series A funding of USD 6.7M. Stonebridge Ventures, LB Investment, DS Asset, Intervest, and Company K Partners joined the series B funding round. So far, we have raised a total of $23M in investment funding.
We offer unique opportunities to work on cutting edge technologies related to AI and model compression. We value inclusivity and autonomy and encourage our team members to solve problems and share their own opinions proactively.
Core & Research team is involved in performing research/development for core modules and of Netspresso, On-device ML framework in Nota AI
In detail, we’re conducting research/development toward Lightweight AI model for on-device deployment
We’re targeting AI models with state-of-the-art performance for directly implementing into NetsPresso as well as publishing qualified publications AI models. It can allow to directly utilize multiple computer vision downstream tasks in Nota AI
Now, we’re actively collaborating with other ML/DL Research Engineer, Frameworks Engineer, Embedded Engineer from each module (Model Searcher, Model Compressor, and Model Launcher) at Nota AI
- Active research and development
- Experienced in deep learning model compression (Pruning, NAS, etc.) High experience in Python
- Implementation with deep learning frameworks (PyTorch, MxNet, Tensorflow, etc.)
- Ability to research and analyze related preceding research papers
- Good communication skill
- High level of performance evaluation and paper survey
In addition, it would be nice if you bring
- Experience in extra ML tools (e.g. huggingface, mmcv, etc.)
- Experience in ML competition
- Experience in submitting papers related to deep learning model compression techniques and efficient modeling
- Experience in converting AI models into TensorRT, TensorFlow Lite, etc.
What we offer:
- Hands on learning in AI product development, business shaping and processes
- Small team with lots of opportunities to grow and take on responsibilities
- Flexible and inclusive working environment
How to apply:
Please send your CV to email@example.com