Nvidia Senior Data Processing Platform Engineer 

United States, Texas 

604392138

As a data processing platform engineer, you will design, implement and operate Kubernetes based GPU accelerated data processing service at scale, with high availability and reliability. You will lead and encourage adoption of the 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 enterprise scale data science platform.

What you’ll be doing:

• Optimize distributed computing infrastructure by analyzing cost and right sizing for latency and performance

• Identify KPIs and instrument metrics tracking for dashboards and alerting

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

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

• Participate in on-call rotation, run-book implementation and continuous process improvement

What we need to see:

• Experience architecting, developing and deploying large-scale distributed systems at scale

• Strong Kubernetes experience on-premise and/or CSP, developing containerized microservices

• Hands on experience in the performancetuning/troubleshootingSpark applications

• Experience with distributed systems, databases, and big data systems like Ray, Spark Rapids

• Familiarity with metrics collection, health monitoring, and observability tools

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

• Master's or Bachelor's degree in Computer Science or Electrical Engineering or CE or equivalent experience.

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

Ways to stand out from the crowd:

• Prior data processing at scale on Nvidia GPUs

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