Job Description :
Responsibilities
Design and implement systems to run GPU-based compute tasks in a Containers as a Service (CaaS) infrastructure.
Develop workflow management tools to schedule data analytics tasks on available GPU hardware for internal and vehicle-facing workloads.
Develop software to manage and extend Kubernetes as an integrated container execution environment.
Provide expert guidance about implementing and optimizing GPU-based data processing pipelines
Qualifications
Experienced software engineer with a passion for large-scale distributed compute infrastructure.
Hands-on experience with virtualization and container technologies like: Docker, Kubernetes, OpenStack, VMware vSphere.
Detailed experience developing GPU-based data analytics and machine-learning applications using common frameworks such as: CUDA, OpenCV, MVCC, Cafe, Torch, Keras, and TensorFlow.
Demonstrated development experience with languages including: Scala, Java, Python, Golang.
Systems-level experience with Linux Operating System.
Experience building large-scale distributed infrastructure systems.
Demonstrated ability to work in a collaborative, data-driven, start-up environment.
Bachelor’s degree required. Graduate degree preferred.
5+ Years of Experience
Preferred Qualifications
Previous experience in the automotive industry is preferred, but not required.

Client : nio