Full-Time

Principal Data Scientist

Accelerated Apache Spark

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$272k - $425.5kAnnually

+ Equity

Expert

Santa Clara, CA, USA

Category
Data Science
Data & Analytics
Required Skills
LLM
Scikit-learn
Agile
Python
Data Science
Tensorflow
Pytorch
Apache Spark
Machine Learning
Pandas
NumPy
Requirements
  • BS, MS, or PhD in Data Science, Statistics, Computer Science, Computer Engineering, or closely related field (or equivalent experience)
  • 12+ years of work or research experience, with 5+ years as technical lead, in ML model development
  • 2+ years of hands-on experience with Apache Spark
  • Proven technical skills in crafting, implementing, and productionizing high-quality ML solutions
  • Proven ability to use modern techniques and tools for all aspects of ML model development, deployment, and maintenance
  • Excellent programming skills in Python and Python data science related libraries like numpy, pandas, scikit-learn, scipy, pytorch, and tensorflow
  • Experience developing boosted tree model based solutions, using libraries like XGBoost
  • Background in developing LLM/GenAI based solutions
  • Experience in feature engineering and feature importance assessment
  • Familiar with agile software development practice
Responsibilities
  • Develop ML models to predict the performance of GPU accelerated Apache Spark on existing workloads
  • Develop ML models to tune GPU accelerated Apache Spark configurations to optimize performance on specific workloads
  • Work on systems that continuously adapt and improve the aforementioned ML models
  • Work on ML/AI agents that can help fix and optimize GPU accelerated Apache Spark applications
  • Work on new functionality for GPU accelerated Apache Spark to facilitate large scale ML model training and inference
  • Create examples showcasing how to best use GPU accelerated Apache Spark and Spark MLlib to carry out large scale ML and DL training and inference
  • Work with NVIDIA partners and customers on deploying GPU accelerated Spark ML algorithms in cloud or on-premise
  • Keep up with published advances in ML systems and algorithms
  • Provide technical mentorship in data science and ML to a team of engineers
Desired Qualifications
  • Knowledge of architecture of Apache Spark is a strong plus
  • Familiarity with NVIDIA GPUs and CUDA is a strong plus
  • Experience coding in Scala, Java, and/or C++ is a strong plus
  • Able to work well with multi-functional teams across organizational boundaries and geographies

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their main products are GPUs that enhance gaming experiences and support professional applications, along with AI and high-performance computing platforms tailored for developers and data scientists. NVIDIA differentiates itself from competitors by focusing on advanced technology and continuous innovation, ensuring their products meet the evolving needs of users. The company's goal is to lead in AI and HPC solutions, providing powerful tools and services that enable clients to achieve immersive experiences and drive advancements in their respective fields.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Acquisition of VinBrain enhances NVIDIA's AI-driven healthcare solutions.
  • Investment in Nebius Group boosts NVIDIA's AI infrastructure capabilities.
  • Partnership with Serve Robotics aligns with NVIDIA's focus on robotics and AI applications.

What critics are saying

  • Increased competition from AI startups like xAI challenges NVIDIA's market position.
  • Serve Robotics' rapid expansion may lead to financial strain if market growth lags.
  • Integration challenges from VinBrain acquisition may affect NVIDIA's operational efficiency.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.
  • The Omniverse platform enhances NVIDIA's capabilities in industrial AI and digital twins.
  • NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

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Benefits

Company Equity

401(k) Company Match