Overview
On Site
USD 148,000.00 per year
Full Time
Skills
Art
High Availability
Data Science
Real-time
Workflow
Reliability Engineering
Continuous Improvement
Message Queues
Apache Kafka
RabbitMQ
Apache Spark
Machine Learning Operations (ML Ops)
Training
Software Development
Software Engineering
Mathematics
Computer Science
Data Processing
CUDA
Machine Learning (ML)
Recruiting
Promotions
SAP BASIS
Law
Job Details
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:
What we need to see:
Ways to stand out from the crowd:
The base salary range is 148,000 USD - 235,750 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.
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 - 235,750 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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.