Job Responsibilities
Build machine learning infrastructure that allows research scientists to move faster in every step of ML. Build and maintain automated pipelines for training, storage, validating, serving, and monitoring of ML models. Enable rapid experimentation and feedback loops in our model serving code to continuously improve. Job Requirements
Bachelor’s, Master’s, PhD degree or equivalent related professional experience. Minimum 3 years of software engineering experience. Proficiency with
Python , preferably in an ML context. Familiarity with backend technologies, e.g.,
SQL Database ,
Nosql ,
cache ,
message queue , etc. Experience with
Kubernetes
is a must. Familiarity with
CI/CD
and
DevOps
concepts. Familiarity with tools in MLOps, such as
KubeFlow ,
AWS Sagemaker ,
MLFlow , etc. Experience with training, evaluating, and deploying machine learning models is an added plus.
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