Senior Machine Learning Engineer (PhD level)
At Gisual, we are developing infrastructure intelligence technology to eliminate all connectivity outages. Currently, Gisual aids service providers in diagnosing outages through automation. We collaborate with some of the world's leading brands, including AT&T, Windstream, Microsoft, Frontier, General Dynamics, amongst others.
To realize a future without internet outages, we, as a company, aim to recruit leading experts in the field of AI. For instance, one of Gisual's AI experts has created an open-source model capable of detecting 28 different emotions from plain text, currently this model has 10 million downloads. This is just one example of the exceptional team we have assembled at Gisual.
We also believe that to achieve this ambitious mission, we must work together as one cohesive team, in person. Gisual's Laboratory is located in King of Prussia, PA.
The models we are developing are employed by the largest enterprise organizations on Earth; the intelligence derived from these models facilitates real-time automated decisions to power the operations of modern connectivity (internet and phone).
Gisual is experiencing exponential growth. We boast a world-class team, a premium product, and incredible customers.
As a senior machine learning engineer at Gisual, you will hold a prominent position within the company, responsible for making critical decisions.
We are seeking an enthusiastic senior machine learning engineer who desires to work in an early-stage startup environment, ready to exert effort to build the world's best infrastructure intelligence technology.
The ideal candidate possesses:
- Knowledge and experience with time series analysis.
- Experience with APIs.
- Distribution shift experience.
- Missing data expertise.
- Electric grid knowledge.
- Recurrent Neural Network expertise. While not mandatory, familiarity with this is beneficial.
Responsibilities:
- Design, develop, and test new machine learning models with minimal to no retraining for other use cases.
- Utilize machine learning methods such as classification, clustering, regression, and ranking to solve core problems and deliver unique insights.
- Select and prepare appropriate data sets before performing data collection and modeling.
- Perform effective feature selection and engineering, and conduct machine learning tests and experiments.
- Perform statistical analysis and fine-tune test results.
- Train and retrain models as necessary.
- Enhance the accuracy of existing machine learning models.
- Identify and implement new applications for machine learning in the business.
- Research and collaborate with the team to capitalize on new trends in the machine learning space.
- Propose and implement improvements to the machine learning engineering infrastructure.
This position in a in person role with flexibility to work remote when needed. Come join us to building infrastructure intelligence that will eliminate all connectivity outages.