Swarm Analytics develops revolutionary AI technology for transforming cameras into smart sensors. It is able to extract real-time information from video streams directly at their source with unparalleled efficiency.
You will be part of the engineering team and work closely with our data and software engineers (C++). Together we build faster, smarter, and more affordable computer vision-based systems for smart cities. You will be involved in building production-grade training systems, model architectures, scalable training-environment in the cloud, and model optimizations.
- Define and push the technology stack for Atlas (Swarm training platform)
- Build model architectures for detection and classification systems using state of the art research
- Employ state of the art model compression techniques, hyperparameter search, and NAS to optimize for target platforms
- Build a production-grade training system (based on Pytorch) for scalable multi GPU and distributed training in the cloud
- 2+ years of professional experience as a Deep Learning Engineer
- 2+ years of professional experience in software engineering (shipped software to production)
- Professional experience in software engineering (shipped software to production)
- Profound knowledge of Pytorch/Tensorflow (or similar), CNN backbones, detection systems, inference engines, model compression, ONNX, hyperparameter-/network architecture search
- Experience with scalable cloud environments, Multi GPU and distributed training, and training large data sets
- Experience with UNIX based systems, test-driven development, docker, CI/CD
- Starting date as soon as possible
- Permanent full-time contract (38,5h/week)
- Flexible working time
- An office in the heart of the Alps (okay, that's not our merit, but still great!)
- An annual minimum wage starting from 53.000EUR gross
We look forward to receiving your application directly online via our website: https://www.swarm-analytics.com/jobs/deep-learning-engineer/
You can find more information on our homepage and social media channels.
If you have any questions, please read the FAQ on our careers page or contact our People & Culture Manager Sarah Nobis at email@example.com.