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Senior Deep Learning Engineer
1 month ago
- Masters or PhD in CS / EE or equivalent with stellar academic performance
- 6+ years of Deep Learning experience in a corporate environment
- Significant experience training Convolutional Neural Networks (CNNs)
- Experience with Keras (Tensorflow) / Pytorch
- Training Deep Learning Computer Vision (DL CV) applications in a corporate environment
- Startup mentality, team player and strong work ethic to completing assigned tasks and projects within established deadlines
- Published research in peer-reviewed journal is a huge plus
Who We Are
Focal Systems is the industry leader in retail AI solutions. We are a Silicon Valley based startup that has more than doubled in size every year since inception. We are a Deep Learning first company. Our mission is to automate and optimize brick and mortar retail using deep learning computer vision. Focal Systems has been deployed at scale with the top retailers in the world.
What we are looking for
We are looking for a versatile engineer who has demonstrated capabilities to develop, benchmark, and validate a wide variety of deep learning models to achieve target F1 scores / mAP scores. Emphasis of the work will be on Temporal and Computer Vision models.
We have a very strong team of Engineers in Poland.
***Our pay bands are driven by market benchmarks in the target geography for hiring. Our posted ranges typically include multiple job levels. A candidate's level is determined by their performance throughout our talent acquisition process including technical screens, behavior interviews, presentations, work samples, and references. We will communicate transparently with the candidate at final stages regarding how we have leveled them, and what salary range that places them into. Placement within range is equally determined by education, general experience in your profession, specific experience in our domain, and your performance in the talent acquisition process. It is rare to receive an offer at the top of the range for a role.
,[Develop state-of-the-art and novel deep neural network architectures, Develop training & testing pipelines to assess the performance of architectures on relevant image processing tasks, Keep up with deep learning literature and research publications in order to implement the latest techniques into our networks and pipelines, Develop machine-learning algorithms on a breadth of software frameworks (Keras, TensorFlow, Torch) and deploy on a diversity of hardware platforms] Requirements: Python, Machine learning, TensorFlow, Keras, PyTorch, OpenCv, Computer Vision, SQL, Cloud, PhD Tools: Jira, Confluence, GIT. Additionally: Training budget, Flat structure, Small teams, International projects, No dress code, Startup atmosphere, In-house hack days.