Position: Deep Learning Engineer
Company: SQUAD
Category: Data Science
Experience required: 2y
English level: upper
Published: 2021-07-01T00:00:00+03:00

**Job Summary**

As a member of our Research Team, you will be engaged in an iterated process of data preparation, prototyping and/or implementation, measurement, and deploying your solution together with the back-end team. You will work closely with members of our Research and Engineering teams to improve models and bring products to the market based on your research.

**Qualifications and Skills**

— 2+ years in machine learning (computer vision domain)
— Practical experience in at least one of the following problems: classification, detection, segmentation.
— Python3, numpy, scikit-learn, pandas, scipy.
— Deep learning frameworks:TensorFlow or PyTorch is a must; Keras is plus.
— Experience in deploying machine learning models to production
— Good understanding of machine learning and deep learning concepts.
— Good written and spoken English

**Nice to have**

— Practical experience with GANs, VAEs
— Probabilistic programming and bayesian framework
— Model optimization: pruning, quantization, knowledge distillation
— Basic understanding of web and client-server architecture asyncio, aiohttp, and other async libraries for back-end
— Basic understanding of Big Data, understanding of difference between MapReduce and in-memory processing
— Algorithms, data structures
— SQL, NoSQL
— Docker, Kubernetes, Kubeflow
— Bash

**We offer multiple benefits that include**

— Working on impactful security products and the opportunity to use them personally
— Competitive salary and perks
— PE accounting and support
— WFH and remote working mode possibility. Partial furniture compensation
— Social package, including medical insurance available from the start date and sports compensation after the trial period
— 18 paid vacation days per year, paid public holidays according to the Ukrainian legislation
— Educational possibilities like corporate courses, knowledge hubs, and free — English classes. Semiannual performance review
— Free meals, fruits, and snacks when working in the office.