NVIDIA
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Our technology has no boundaries! NVIDIA is creating the world’s most groundbreaking and innovative 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 looking for individuals to develop a data processing and ML platform for data scientists to use.
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 performance tuning/troubleshooting Spark 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
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until August 12, 2025.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.
JR1999148
Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
Industries Computer Hardware Manufacturing, Software Development, and Computers and Electronics Manufacturing Referrals increase your chances of interviewing at NVIDIA by 2x Get notified about new Platform Engineer jobs in
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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 performance tuning/troubleshooting Spark 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
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until August 12, 2025.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.
JR1999148
Seniority level
Seniority level Mid-Senior level Employment type
Employment type Full-time Job function
Industries Computer Hardware Manufacturing, Software Development, and Computers and Electronics Manufacturing Referrals increase your chances of interviewing at NVIDIA by 2x Get notified about new Platform Engineer jobs in
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We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr