Machine Learning Engineer (Fully Remote)
Tiger Analytics Inc.
Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. We are looking for a motivated and passionate Machine Learning Engineers for our team.
Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
Creating Scalable Machine Learning systems that are highly performant
Building reusable production data pipelines for implemented machine learning models
Writing production-quality code and libraries that can be packaged as containers, installed and deployed
Bachelor's degree or higher in computer science or related, with 5+ years of work experience
Ability to collaborate with Data Engineers and Data Scientist to build data and model pipelines and help running machine learning tests and experiments
Ability to manage the infrastructure and data pipelines needed to bring ML solution to production
End-to-end understanding of applications being created and maintain scalable machine learning solutions in production
Ability to abstract complexity of production for machine learning using containers
Ability to troubleshoot production machine learning model issues, including recommendations for retrain, revalidate, and improvements
Experience with Big Data Projects using multiple types of structured and unstructured data
Ability to work with a global team, playing a key role in communicating problem context to the remote teams
Python, Spark, Hadoop, Docker, with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design
Test-driven development (prefer py. test/nose), experience with Cloud environments
Proficiency in statistical tools, relational databases, and expertise in programming language like python/SQL is desired.
Knowledge of ML frameworks like Scikitlearn, Tensorflow, Keras, etc.
Knowledge on any of the cloud-native MLaaS offerings like AWS SageMaker, AzureML, or Google AI platform
$100k - $145k per year
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