Lead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes.
Build, administer and scale ML processing pipelines.
Be comfortable navigating the following technology stack: Python3, Pyspark, scripting (Bash/Python), Hadoop, SQL, S3 etc.
Should be able to understand internals of ML models such as Random Forest, CNN, Regression models, etc
Design, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality.
Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks.
We believe in end-to-end ownership; this role will involve taking ML models to production at a scale.
What You’ll need to Succeed:
Bachelor’s degree in computer science /information systems/engineering/related field
8+ years of experience in software engineering with a minimum of 4+ years in ML
Good experience in Pyspark
Expert level understanding of Python with design patterns and object-oriented programming.
Experience debugging and reasoning about production issues is desirable.
A good understanding of data architecture principles preferred.
Any other experience with Big Data technologies / tools
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