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What you’ll be doing:
Automating and optimizing testing of Deep Learning models and AI Services from different data domains with focus on inference
Developing shared utilities for setting up systems, running tests, recording results and visualization on dashboards.
Configuring, maintaining, and building solutions on industry-standard tools (e.g. GitLab, Docker, ElasticSearch etc)
Lead best-practices for building, testing, and releasing software including AI Services and DL models
Identifying infrastructure needs and translating them into action
Building tools for automatic content generation mechanisms that saves dozens of engineering hours
What we need to see:
BSc or MS degree in Computer Science, Computer Architecture or related technical field
5+ years of work experience in software development
Excellent Python programming skills, and a deep understanding of OOP concepts.
Experience in building both back-end services (e.g Flask, FastAPI, Django) services and front-end (e.g. JS, React, Vue, Dash, Streamlit)
Understanding of Deep Learning on the level that allows benchmarking DL models
Familiarity with DevOps concepts such as CI/CD, Docker, Jenkins, and automation tools.
Strong time-management and organization skills for coordinating multiple initiatives and priorities.
Ability to utilize new technologies and products in very complex projects.
Good communication and documentation habits
Ways to stand out from the crowd:
Deep understanding of containerization technologies such as Docker
Experience in building monitoring or dashboarding solutions.
Hands-on in configuring complex CI pipelines
Experience with HPC based compute clusters and scheduling solutions like Slurm or familiarity with orchestration tools such as Kubernetes
Hands-on experience working in cloud environment
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