Working at FeatureX
FeatureX uses AI to discover meaningful patterns in the world's data. We use computer vision, deep learning and statistical machine learning to extract useful patterns that occur over time and present this information in a manner that is both valuable and easily understandable.
We attract scientists and engineers with a true passion for data. We seek individuals who want to build for today and invent for tomorrow. If you join us, you’ll have the freedom to approach, own, and solve problems creatively.
As a machine learning research scientist, you will be developing machine learning techniques for a wide variety of data sources, ranging from financial time series data to features extracted from satellite imagery. You will be engaged with projects that use both supervised and unsupervised learning. You will be diving into new data sets and should assume that no data source or technique is off-limits.
Skills and Requirements
A successful candidate will have some or all of the following attributes:
- MS or PhD degree in computer science or other quantitative disciplines
- Demonstrated ability to create, invent, and be innovative
- A theoretical grounding in statistics and statistical machine learning
- Ability to work both independently and collaboratively in a fast-paced research environment
- Enthusiasm for pursuing new challenges and technologies
- Intermediate programming skills in Python and Java
- Expert knowledge of recurrent neural networks and other deep learning algorithms
- Expert knowledge of evolutionary computation techniques
- Strong grounding in mathematical optimization
- Experience with using deep learning frameworks such as Tensorflow, Theano, Caffe
- Publications in machine learning conferences and journals
- Open source contributions
1. We are now hiring intern positions for this type of role. If you are seeking an internship, please indicate this clearly and specify the dates of your availability.
2. We're currently only hiring people who are able to work in the United States.