Description

Job Title: Machine Learning Engineer

We are looking for a software engineer with strong cloud DevOps skills to join our Data Science Department as a Machine Learning Engineer. You will work on automating, building and deploying production machine learning solutions. You will have the opportunity to work alongside Machine Learning Engineers, Researchers and Analysts within our Data Science team who together create solutions that power innovation and drive revenue growth for Dstillery.

The Machine Learning Engineering team often tackles greenfield projects and we are in the midst of building exciting new products on top of a modern, cloud based machine learning platform, making it an exciting time to join and help shape our future machine learning products.

We believe diverse voices and backgrounds lead to richer perspectives and more innovative products. We strive to be a welcoming, safe and inclusive place to work that takes work life balance seriously and gives you the flexibility and support to be happy and productive. We value a diversity of professional backgrounds, and our colleagues come from various settings such as academia, fintech, adtech, big tech companies, startups, etc.

As a Machine Learning Engineer here is what you’ll learn and do

• Develop our MLOps processes and tools
• Collaborate with researchers and other machine learning engineers to build exciting new machine learning products
• Explore, build and deploy machine learning infrastructure at scale.
• Write production code and data pipelines and conduct code reviews.
• Promote and exemplify best practices of engineering and data science throughout the organization.

You’ll have

• A bachelor’s degree in a quantitative field (CS, EE, Statistics, Physics, Math, etc.)
• 2+ years of industry software engineering experience.
• Passion for clean code, building, and automation.

Technologies we use

Dstillery anticipates all candidates will need some sort of on-the-job training and a willingness to learn through collaboration is key. We understand that you may not already be an expert in the various technologies we use, but you should be ready to learn and work with:

• Google Cloud Platform
• Python
• Machine learning frameworks such as scikit-learn, TensorFlow, PyTorch
• Airflow, Spark, SQL, Kubernetes, JenkinsX, Terraform

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