NextEV is hiring a

Senior Engineer, Embedded Modeling and Prediction

San Jose, United States
Full-Time

As a NEXTEV Engineer in the Machine Learning team, you will have the extraordinary opportunity to apply leading edge research to revolutionize the automotive domain.
 
You will utilize your expertise in machine learning to model the complex environment both inside and outside the vehicle, and use the model to predict and to provide intelligent actions. The resulting experiences will provide greater comfort, convenience, personalization, and safety for both vehicle occupants and the public at large.

Responsibilities
 
Assess the latest developments in predictive modeling from both research and industry to select the most promising development directions for potential use-cases.
 
Tightly integrate with cloud intelligence and work with a massive amount of in-vehicle data to create accurate models of the driver and the vehicle.
 
Leverage embedded computing resources and software platforms to maintain the models and run predictive algorithms in real-time.
Through a cycle of continual experimentation, refinement, and optimization bring the solutions to practical, deployable embodiments in vehicles and production cloud services.
 
Requirements
 
Bachelors, or Masters in computer science, computer engineering, applied mathematics or related field with a focus on machine learning.
 
5+ years of industry experience.
 
Three plus years of applying machine learning and predictive modeling techniques to real-world scenarios. Experience should include knowledge of feature identification and extraction, and knowledge of statistics and neural network based algorithms.
 
Proficiency in Python and C++.
 
Familiarity with modern software development tools for source code control, unit testing, automated build, test, and deployment.
 
A passionate, curious mind that is driven to find solutions to difficult problems. A capability to work either independently or collaboratively as projects evolve.
 
Desirable Attributes:
 
Experience with machine learning frameworks such as Scikit-learn, Caffe, Torch, Theano, or TensorFlow.
 
Experience with large scale training using cloud services.
 
Experience GPU acceleration of computer vision algorithms via CUDA or OpenCL.
 
Experience with embedded Linux systems, and/or mobile platforms (Android, iOS).
 
Experience with the automotive domain.