Xavor’s vision is to leverage disruptive technologies to make the highest level of business impact to traditional businesses. We believe that over the next 10 years, there will be tremendous convergence between traditional and digital world – both in services they deliver and products they make. This will lead to disruption in business models, where products transform into service and value shifts to platforms and data. Our vision is to participate in this value creation not only as service provider but also as risk-taking innovation partner. Our focus areas include AI/machine learning, mobile, IIoT, cloud computing, UX design, mobility, and embedded engineering.

Required Skills:

• Creating and maintaining a framework for deploying machine learning algorithms and maintaining a framework for deploying machine learning algorithms.

• Possess leadership qualities to drive and take ownership of projects

• Liaise with stakeholders to analyze business problems, clarify requirements and define the scope of the resolution needed.

• Experience in optimizing deep learning models to save time and memory requirements in both training and inference phases (TensorRT, Tensorflow lite).

• Experience in Deep Learning techniques for object detection and tracking.

• Knowledge in the latest CV related algorithms and methods such as GAN variants, 3DPose Estimation, Face Recognition and Segmentation.

• Proficiency with Python and experience with data processing tools (e.g., scipy, numpy, pandas) • Experience with training, fine-tuning, and modify models using popular deep learning frameworks (PyTorch, Tensorflow, Keras).

• Experience with one of the Cloud Services: Azure, AWS, Google Cloud • Comfortable with ssh, bash, and linux. 

Desirable Skills:

• Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability.

• Use exceptional mathematical skills, in order to perform computations and work with ML algorithms.

• Research and implement best practices to improve the existing machine learning infrastructure. • Experience in computing sensor parameters and relationships to fuse data from multiple sensors.

• Experience working with large datasets to extract entities, select and estimate properties.

• Knowledge in the latest NLP-related algorithms and methods such as sequence-tosequence models, word and sentence embeddings, attention, etc.

• Familiar with version control and containerization (Docker, Kubernetes) 

• 4+ years' experience of relevant industry experience.

• Master's/Bachelor's in Computer Science/Artificial Intelligence/Data Science from a renowned university. 

• Expertise with at least one deep learning framework (PyTorch, TensorFlow, or equivalent)