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Senior MLOps Engineer

ABOUT FUSEMACHINES

Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic and more than 250 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.

ABOUT THE ROLE

This is a remote position 

ABOUT YOU

  • 5+ years of experience in MLOps
  • 3+ years experience working on machine learning pipelines 
  • A passion for automating everything
  • Experience with Azure cloud services: Azure VMs, Azure Databricks, SQL Database, SQL Data Warehouse
  • Technical expertise in one or more of the following: Python, C/C++, SQL, Databricks, Azure cloud environments
  • Familiarity with meteorological data formats (NetCDF, GRIB, BUFR) is a desirable
  • Familiar with time-series analytics
  • Familiar with deep learning algorithms such as CNN, RNN 
  • Familiar with Pytorch, Tensorflow, Sklearn, XGBoost
  • Familiar with data pipelines
  • Familiarity with meteorological data formats (NetCDF, GRIB, BUFR) is a desirable

Responsibilities: 

  • Lead and drive MLOps projects from beginning to end
  • Collaborate with our team of data scientists, data engineers, and scientists to support optimization, scalability, and deployment of innovative Machine Learning technologies
  • Frame and structure questions, collect and analyze data, research, prototype, and build machine learning pipelines, and runtime services of models in production
  • Have a strategic perspective of how several machine learning solutions come together against a team, technical product strategy, and lead to an optimal sequence of work
  • Excellent communication skills with demonstrated experience driving teams forward and the ability to influence technical decisions to line up with the company’s strategy

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

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