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 full-time, remote position.
ABOUT YOU
* 5+ years of experience in DevOps/MLOps
* 3+ years experience working on machine learning pipelines
* A passion for automating everything
* Strong AWS cloud experience
* Familiar with time-series analytics
* Familiar with deep learning algorithms such as CNN, RNN
* Familiar with Pytorch, Tensorflow, Sklearn, XGBoost
* Familiar with data pipelines
* Familiar with AWS Sagemaker
* Familiar with one or more: auto encoding, multivariate time series, ARIMA, MQ-RNN, NLP, Computer Vision, ES-RNN, n-beats
Responsibilities:
* Lead and drive MLOps projects from beginning to end
* 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.
Fusemachines focuses on Enterprise Software, Machine Learning, Artificial
Intelligence, and Natural Language Processing. Their company has offices in
New York City and Nepal. They have a mid-size team that's between 51-200
employees.
You can view their website at <https://www.fusemachines.com> or find them on
[Twitter](https://www.twitter.com/fusemachines),
[Facebook](https://www.facebook.com/fusemachines), and
[LinkedIn](https://www.linkedin.com/company/fusemachines).
