ML-Ops Engineer

What will you do?

• Work closely with algorithms teams to build machine learning infrastructure.

• Take responsibility for end-to-end design of APIs, methodologies, processing pipelines and integration with internal customers and tools.

• Help establish best practices and a culture of excellence in deploying maintainable data and model pipelines.

Requirements:

• B.Sc. in computer science or related STEM degree.

• At least 5 years SW industry experience including MLOps roles.

• High proficiency in Python and C++.

• Strong understanding of the MLOps technological landscape, software testing methodologies and continuous integration tools.

• Strong communication and interpersonal skills.

• Ability to effectively communicate across multi-disciplinary teams, translate discussions into robust software tools, designs and guidelines.

Advantages

• Hands-on experience with low-level internals of machine learning frameworks including quantization and deployment of machine learning models to embedded platforms and setup of distributed systems for training of ML models.

• Experience with Pytorch/cmake/docker/git/Linux/GPUs/quantization/job-schedulers and CI/workflow tools.

• Experience with web applications.

• Able to profile performance issues.