Nvidia Senior Data Processing Platform Engineer 

United States, Texas 

707148823

As a data processing platform engineer, you will design, implement and operate K8s based event driven data processing service at scale, with high availability and reliability. You will lead and encourage adoption of the event driven data processing service, your work should improve time to first query (TTFQ) metrics, drive platform engagement metrics, and come up with innovative solutions that blends with pioneering Nvidia's LLMOps / DataOps enterprise scale data science platform.

What you’ll be doing:

• Build, maintain event driven data processing service with scale-to-zero, auto-scaling features

• Implement event driven APIs and integrate with company's broader engineering systems

• Enhancing and maintaining a robust scale, cost optimized, real-time data processing service

• Train data engineers, data scientists and production engineers how to adopt event driven data processing workflows

• Participate in on-call rotation, site reliability engineering, run-book implementation and continuous improvement

What we need to see:

• Experience in designing event driven architecture for data processing

• Strong K8s experience on-premise and/or CSP, Dockers, Kubeflow

• Data processing tools experience - message queues like Kafka, RabbitMQ, Distributed compute like Ray, Spark

• Experience implementing and/or deploying eventing services like Argo events, Knative

• Knowledge of MLOps and Data Ops lifecycle - feature engineering, training, validation, tracking, inferencing, experimentation, monitoring, security, Lambda processing, SAGA patterns

• Building, operating and maintaining full stack software deployments coupled with excellent software programming skills

• A minimum of 5yrs experience with a background in software engineering and math

• BS or MS in Computer Science or equivalent program from an accredited University / College or equivalent experience

Ways to stand out from the crowd:

• Prior data processing at scale using event driven architecture on GPUs

• Experience with CUDA and/or using Nvidia GPUs for ML/DL