Our cutting-edge, well-funded AI-DeepTech Start-Up based in Berlin is looking for a Deep Learning Engineer who is ready for the challenge of building world-class on-device AI technology.
You will join our world-class engineering team (ex-Facebook, ex-Amazon, Cambridge, etc.) to help us stay on top of the latest developments in the Computer Vision Deep Learning space.
You will be part of an amazing innovation-driven growth story:
We are pioneers in the field of embedded & mobile AI inference applications, repeatedly tackling technical challenges as the first in the world. Over the last 5 years, we have built up a mature tech stack that allows us to develop and deploy new applications within weeks.
We are product-driven and have already three products in production.
We look for highly motivated and curious minds - striving to become true experts in their respective fields. Hence, we offer the flexibility that you need to contribute - we offer you to work on-site or in a hybrid manner.
We are and always have been a very international team.
We are fast and agile. We break things if needed to improve and adjust fast. No hierarchy, no walls, no politics. At the end of each week, we see our progress. We discuss, we plan, and then execute; all together and in respect of each other’s contribution.
Here’s what we are looking for:
We are looking for a Deep Learning Engineer to support the ML team in bringing state-of-the-art machine learning models to production.
We work on object detection, scene understanding, self-supervised learning, representation learning, model compression, efficient architectures, and many other exciting topics.
You will contribute to a broad spectrum of topics ranging from implementing research ideas over improving our training and deployment pipelines to enhancing our data quality and efficiency.
You will cover all phases of the ML life cycle and production-grade development
Assess and solve new ML use cases
Go from scoping & design to production
Build and improve our internal ML framework
Automate and stabilize our training, evaluation, and deployment pipelines
Build new ML models and efficient architectures
Improve our model compression technology
Build tools and use the tools you build
Exploratory data analysis, auditing, build tools for auto-labeling
Maintain and extend our ML data pipelines
Manage our on-premise and cloud storage and compute resources (GCP)
Required Skill-Set
We value intelligence, curiosity, and a solution-driven mindset higher than existing skills.
Still, for this role, we expect you to have experience in:
Software engineering (Python)
Deep Learning for Computer Vision
PyTorch
Parameter/model studies, managing experiments
On the side: SQL, Git, Linux
Additionally, it would be great if you already have experience in any of the following:
Computer Vision
Understanding and implementing research papers
Efficient Deep Learning / Model Compression / Knowledge Distillation
PyTorch Mobile / ONNX & ONNX Runtime
CI / CD
Docker / Containers
Cloud storage and compute
