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Deep Learning Backend Engineer

As a Deep Learning Backend Engineer, you will:

Write clean, concise, modular code that is easily testable.
Participate in an agile environment.
Participate in the full software development lifecycle (requirements gathering, designing, building, testing and maintenance).
Participate in code reviews.

What we look for:

B.Sc / M.Sc Computer Science or equivalent.
Strong team player with excellent communication skills in verbal and written English.
Skilled in Go, Python or NodeJS [Go is an advantage].
Experience working with Linux.
Experience working with Cloud [AWS is an advantage].
Experience working with SQL/NoSQL.
Experience working with Docker and Orchestration.
Experience building large and scalable applications.
Understanding of unit, integration, and end-to-end testing.
Experience with continuous delivery and automated testing.
Familiarity with Frontend Development.
Basic knowledge in Machine Learning.

Deep Learning Engineer

As a Deep Learning Engineer, you will:

Work closely with our researchers and product team to design, develop, test, deploy, maintain, and improve new neural network models over standard and edge accelerators.
Build custom loss functions, design complex layers, and manipulate tensors.
Manage individual customer projects. Handle priorities, deadlines, and deliverables, and conduct frequent interactions with our customers’ highly-skilled deep learning engineers.
Build the core software elements that drive the Clika products.
Write clean, efficient, and well-documented code.

What we look for:

B.Sc / M.Sc Computer Science or equivalent degree.
Strong team player with excellent communication skills in verbal and written English.
Experience working with Linux.
Experience working with Git.
Experience in developing Deep Learning models.
Extensive knowledge of OOP, design patterns, and solid software development principles in Python.
Experience working with at least one major ML framework (Tensorflow/PyTorch).
Experience developing in C++
Experience implementing advanced ideas from academic papers and turning them into production-ready code.

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