Our technology has no boundaries! NVIDIA is building the world’s most groundbreaking and state of the art compute platforms for the world to use. It’s because of our work that data engineers and data scientists can advance their ideas. We are building a team who will be developing data processing and ML platform that can be used by data scientists to run large scale workloads and promoting a culture of MLOps.
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
The base salary range is 148,000 USD - 230,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
